Improved Compact Cuckoo Search Algorithm Applied to Location of Drone Logistics Hub

: Drone logistics can play an important role in logistics at the end of the supply chain and special environmental logistics. At present, drone logistics is in the initial development stage, and the location of drone logistics hubs is an important issue in the optimization of logistics systems. This paper implements a compact cuckoo search algorithm with mixed uniform sampling technology, and, for the problem of weak search ability of the algorithm, this paper combines the method of recording the key positions of the search process and increasing the number of generated solutions to achieve further improvements, as well as implements the improved compact cuckoo search algorithm. Then, this paper uses 28 test functions to verify the algorithm. Aiming at the problem of the location of drone logistics hubs in remote areas or rural areas, this paper establishes a simple model that considers the trafﬁc around the village, the size of the village, and other factors. It is suitable for selecting the location of the logistics hub in advance, reducing the cost of drone logistics, and accelerating the large-scale application of drone logistics. This paper uses the proposed algorithm for testing, and the test results indicate that the proposed algorithm has strong competitiveness in the proposed model.

Introduction
There are many complex optimization scenarios in the fields of industry, finance, mathematics, etc. Some of them are difficult to find a true global optimal solution. The meta-heuristic algorithm is suitable for dealing with problems that are not solved by specific effective methods [1][2][3][4]. The Cuckoo Search (CS) algorithm is a new heuristic algorithm that simulates cuckoo parasitic brooding and solves complex optimization problems [5,6]. The CS uses the nest position of the cuckoo bird to represent a possible solution in the solution space. The cuckoo bird's parasitic brooding behavior is used to search the solution space of the complex optimization problem. The movement of the solution is realized by the cuckoo's Levy flight mechanism, and the potential better solution is found through continuous searching and updating. The Levy flight mechanism used in the cuckoo algorithm can effectively jump out of the local optimal solution, and thus has better global search performance. It has also achieved better results in engineering optimization problems [6,7]. Since the cuckoo algorithm was proposed, various improved versions of the algorithm have been proposed for different uses, such as Modified Cuckoo Search (MCS) [8], Binary Cuckoo Search (BCS) [9], Multiobjective Cuckoo Search (MOCS) [10], Chaotic Cuckoo Search (CCS) [11], etc. This type of algorithm is usually used to solve complex optimization problems, thus it will set a population to obtain better solutions in a shorter time. Therefore, when dealing with complex optimization problems, or when it is applied to a device with limited memory, the heuristic algorithm needs to be improved to achieve the same or better solution in a shorter time or with less memory consumption.
Compact is a technique that can reduce the memory usage of the meta-heuristic algorithm. By using a probabilistic model to replace the population used in the algorithm from a macro perspective, it achieves less memory usage and shorter calculation time [12][13][14][15][16][17][18]. The compact method uses a probability model to represent the original population, and then uses the probability model to generate a new solution. By comparing the generated solutions, the probability model is updated, which is then used to replace the population update in the original algorithm [12]. Some related algorithm improvements using the compact method have been proposed, such as compact particle swarm optimization (cPSO) [12], compact genetic algorithm (cGA) [13], compact differential evolution (cDE) [14], compact bat algorithm (cBA) [15], etc. This article attempts to implement an improved version of the compact CS algorithm with a mixture of normal and uniform distributions. For the problem of weak search ability of the algorithm, this paper combines the method of recording the key positions of the search process and increasing the number of generated solutions to achieve further improvements and implements the improved compact cuckoo search algorithm (icCS). The algorithm was tested using 28 test functions of CEC2017.
As a new logistics method in the supply chain, drone logistics can effectively improve the efficiency of the logistics system and solve the problem of express delivery in the last mile of the current logistics system [19,20]. Drone logistics, with its own advantages, can perform express delivery in rural, mountainous, or congested areas, as well as areas where ground traffic is impassable [20]. It can also be used in special situations and applied to scenarios that require rapid delivery, such as medical rescue and blood product transportation [21][22][23][24]. To apply drones to logistics systems, there have been many related studies. In addition to optimizing the design of logistics systems and logistics drones [25], it is also necessary to design logistics models based on cost, efficiency, and other factors. Flight optimization in the process of logistics distribution of drones is also an issue that needs to be researched in the field of drone logistics [26]. There are currently two main models of drone logistics: models for distribution centers and drones and those for delivery vehicles and drones. Many scholars have studied the logistics mode of combining drone and truck transportation [27,28]. For the model of using truck transportation and drone for distribution, the logistics problem is usually regarded as a path planning problem with the drone [29]. Then, usually the travelling salesman problem is used to solve it on the basis of adding drones [30]. Intelligent algorithms are also applied to such problems [31]. In addition, there are many studies using machine learning to deal with supply chain problems. Some machine learning methods, such as Bayesian optimization, can also effectively deal with optimization problems [32,33]. The logistics mode of distribution centers and drones usually focuses on the location of the logistics center, and, because of the low load of the drone itself and the limited battery energy, the logistics of the drone are limited [34]. In addition, other scholars have studied other influencing factors of drone logistics, including operating costs, differences between urban and rural areas, etc. [35,36].
Hu et al. [37] used CS to deal with the trajectory planning of micro aerial vehicles for express transportation in cities. Considering the wind field, the obstacles of the building, and the characteristics of the goods, the cuckoo algorithm is used to plan the transportation path. This paper focuses on rural and remote areas, where surrounding villages are served by setting up a drone logistics hub. The path of the drone during transportation is a straight line between the logistics hub and the village. The main problem is the optimization of the location of the logistics hub. This paper aims at the logistics scenarios in rural and remote areas, using the logistics model of distribution centers and drones, assuming that future logistics drones can or have a stronger load capacity and longer dwell time. Then, the location of the drone logistics hub is simply modeled and tested using the algorithm proposed in this paper.

Related Work
This section briefly introduces the cuckoo search algorithm and the drone logistics hub location model proposed in this paper.

Metaheuristics Algorithm of Cuckoo
The CS algorithm is a new meta-heuristic algorithm that simulates the breeding strategy of cuckoo in nature [5]. It solves complex optimization problems by imitating the brooding and parasitic behavior of cuckoos in nature. The cuckoo search algorithm uses the position of the bird nest to represent a possible solution, and updates the solution by updating the position of the bird nest. The update method uses Lévy flight to simulate the movement pattern of birds in nature. Lévy flight consists of long-range flights with occasional large steps and short-range flights with frequent small steps. The occasional long-distance flight in Lévy flight can expand the search range and prevent falling into local optimum.
To simplify the implementation of this algorithm , three simple and idealized rules are set for the cuckoo search algorithm. (1) Each cuckoo produces only one egg at a time, and then randomly selects a location for hatching. (2) The nest with the best eggs will be preserved and passed on to the next generation. (3) The number of nests that can be used is fixed, and the probability of the eggs in the nest being found is p a ∈ [0, 1] . When the egg is found, the owner of the nest will throwaway the egg or build a new nest. The cuckoo search algorithm uses the parameter p a to control local search and global exploration [38]. The formula for local search is written as where x (t+1) represents the next generation solution, i is a cuckoo in the solution, St is the step size, H(u) is a Heaviside function, is a random number generated by a uniform distribution, and x (t) j and x (t) k represent two randomly selected different solutions from all current possible solutions. The implementation formula for global exploration is written as In Equation (2), α > 0 indicates the step size scaling factor, usually α = 1. The random step size in Lévy flight is generated using the Lévy probability distribution.
The variance and mean of the distribution are infinite. According to the original literature of the CS algorithm [5], the pseudo-code of the algorithm is shown in Algorithm 1.
Compared with PSO, cuckoo search algorithm can achieve global convergence [39][40][41]. Compared to algorithms using standard Gaussian processes, the cuckoo search algorithm is more efficient by using Lévy flights.

Algorithm 1: Cuckoo search via Lévy flights.
Objective fitness function f (x), x = (x 1 , . . . , x d ) T ; Generate initial n bird nests x i (i = 1, 2, 3, . . . , n); while (t< Max Generation ) or (stop criterion) do Generate a random solution using Lévy flights; Calculate and store fitness F i ; Choose a nest among n( say, j) randomly; if F i > F j then Generate new solution and replace j; end A fraction (p a ) of worse nests are abandoned and generate a new solution; Keep the optimal solution in all solutions unchanged; Find the current optimal solution and save; end

Location Model of Drone Logistics Hub
At present, drone logistics is limited by the low load and weak endurance of drones. Moreover, drones have limited mobility and cannot perform long-term continuous delivery, thus the current more reasonable model is the collaborative model of delivery vehicles and drones. Then, path planning for delivery vehicles and drones is performed. However, after the drone picks up the goods from the delivery vehicle for delivery, it is necessary to consider that the drone returns to the delivery vehicle after the recipient receives it. The movement of the delivery vehicle and the uncertainty of the recipient's pickup time will significantly reduce the drone's delivery efficiency. However, with the development of technology, drone equipment for logistics will solve the current problems, and, when the level of automation increases, the mode of combining small unmanned logistics centers with drones will become more competitive.
This paper chooses the model of unmanned logistics center and drone, and applies it to the location of unmanned logistics hub in rural areas. The simulation diagram of the model in two-dimensional space is shown in Figure 1. The premise assumptions and explanations of the model are as follows: (1) The frone only travels to and from one village at a time.
The drone's endurance is able to meet the flight requirements from the logistics hub to the farthest village that the logistics hub is responsible for.
Under ideal conditions, the drone distribution path is a straight line from the logistics hub to the corresponding village. (4) Each logistics hub is responsible for express delivery services in multiple villages, and each village chooses the nearest logistics hub to serve it. (5) The sizes of the villages are different, that is, the areas of the villages and the numbers of villagers are different. (6) Drones do not enter the village when delivering goods, but deliver goods to the edge of the village to ensure safety.
The land transportation distance from the logistics hub to each village is different and the degree of traffic difficulty is measured by the distance.
The number of logistics hubs is artificially set according to the scope of application and artificially selected after calculating different solutions. The circle in Figure 1 represents the village, and the size of the circle represents the radius of the village, which is expressed as R. The triangle represents the drone logistics station, and H represents the straight line distance between the logistics hub and the village center. The model established in this paper is relatively simple. This paper only considers the distribution distance, the size of the village, and the current village's efficiency ratio of using drone logistics to land transportation, which is used to indicate the degree of difficulty of land transportation. The objective function of the model is written as In the formula, H i represents the straight line distance from the center of the village labeled i to the nearest logistics hub. H i − R i is the distance between a village and a logistics hub minus the village radius, as drone delivery is not delivered to the precise location of the recipient, but is delivered to the edge of the village, which can ensure better security. N is the total number of villages to be considered. cp is the number of people living in the village. The larger is the population, the more frequently does the logistics center deliver to the village, thus the logistics hub needs to be closer to the village to reduce the overall cost. L1 is the distance for land transportation, L2 is the distance for linear delivery using drones, and L1 L2 is usually a value greater than 1, thus the logistics hub needs to be closer to villages with high land distribution costs. The variables and parameters involved in the model can be obtained through actual measurement. There are no unnatural parameters, and the degree of traffic difficulty is also obtained by using land transportation distance and straight flight distance. All parameters can be calculated from the application environment data during actual application.The solution obtained after calculating the model is the relative positions of multiple logistics hubs, and different villages choose their nearest logistics hubs based on the distance. In the end, different solutions will be generated according to the number of logistics hubs. Because the proposed model does not take into account all the influencing factors, and the importance of the model's constraints is different in different situations, it needs to be artificially selected according to actual conditions.

Improved Compact Cuckoo Search Algorithm
This section introduces the application of the compact scheme and improved compact scheme to cuckoo search algorithm.

Compact Scheme
The essence of the distribution estimation algorithm (EDA) is to use the probability model to represent the population in the meta-heuristic algorithm, use the probability model to represent the population from a macro perspective, and implement the operation on the population in the meta-heuristic algorithm by operating the probability model [42,43]. The compact method is an effective method to reduce the memory footprint of the meta-heuristic algorithm. By updating the probability model instead of updating the entire population, the calculation amount is reduced and the algorithm running time is shortened.
Firstly, the probabilistic model is constructed using the original population distribution, and then the population is updated by evaluating the probability model to find the optimal solution. Since the probability model is used to represent the entire population, the characteristics of the original population are described from a macro perspective. Perturbation Vector (PV) is often used to represent the characteristics of the entire population. PV is constantly changing with the operation of the algorithm, which is defined as : PV t = µ t , σ t , where µ is used to representing the mean value of the PV, σ is the standard deviation of the PV, and t is used to represent the number of current iterations. Each pair of mean and standard deviation corresponds to a probability density function (PDF), which is truncated at [−1, 1] and normalized to an area of amplitude of 1 [44]. Using the PV vector, the solution x i can be randomly generated by the inverse cumulative distribution function (CDF). After generating two solutions using PV, usually which is better is judged by comparing the fitness function values of the two solutions; the better solution is the winner and the worse solution is the loser. Then, the PV is updated. The formula for updating each standard deviation and the average value in the PV using winner and loser is as follows: where µ t+1 i represents the newly generated average and N p is the virtual population. The update rules for σ are as follows: The PV vector and the generated individual solution are stored during algorithm execution, instead of storing the location of the entire population solution and the motion vector, which achieves less runtime memory usage and is beneficial for use on resource-constrained devices. However, since the conventional compact algorithm only randomly generates one solution at a time, there are fewer possible solutions explored during each iteration, which will cause the problem of insufficient convergence ability in the later iterations, and the method needs to be improved.

Improved Compact Scheme
The compact algorithm saves more memory resources, reduces the amount of calculation, and shortens the algorithm running time compared with the original algorithm. However, the compact algorithm generates two solutions per iteration and compares them. The solution generated during each iteration is less than the population-based method in the original algorithm. Therefore, the number of overall searches is small, the algorithm will converge slowly in the later stages of iteration, and it is easy to fall into a local optimum.
Because the compact algorithm uses PV to generate new solutions, with continuous iteration, PV will slowly converge to a certain area, but the number of solutions generated by PV during each iteration is small, thus it is difficult to jump out of the local optimum. Thus, the method of sampling using the normal distribution in the compact mode is improved. Considering the above problems, this paper chooses to add the uniform distribution sampling method on the basis of using the original compact mode. As shown in Algorithm 2, a new solution is generated using PV during each iteration, and another new solution is generated using uniform sampling. Then, CS is used to update the two generated solutions. Using uniform sampling in the solution space can search for other regions to find a better solution while the PV converges to the optimal region. Because there may be better solutions around the solution generated during the iteration, to get closer to the surrounding better solution during the iteration, a perturbation operation on the optimal value is added in this paper, as shown in Algorithm 2.
Algorithm 2: Improved compact cuckoo search algorithm.
Objective  (5) and (6); end gbestrd = gbest + rand · randn(1, d) //Perturbation//; [winner, loser] =compete(winner, gbest, gbestrd); gbest = winner; t = t + 1; FL = 2 when caught in a local optimal; end else nest randomly walk by Lévy flights; evaluate nest's quality/fitness; A fraction(p a ) of worse nests are abandoned and build a new one; Keep the optimal solution in all solutions unchanged; Find the current optimal solution and save; end if FL==1 then Use gbest to form nestpv i (i ≤ n/2) via Equations (7); Use nestpv and uniform distribution to form the nest; end end After improving the compact mode, the algorithm can achieve better results and convergence ability, but the global search ability and local search ability can still be further improved. Therefore, a switching mode is added in this paper. When the algorithm is trapped in a local optimal value, it switches to a population-based search mode, as shown in Algorithm 2. There are many ways to judge when the algorithm is trapped in a local optimal value. The first method can compare the recent iteration trend with the overall iteration trend. The second method can determine whether a better solution can be found within a certain number of iterations. This paper uses the second method to switch modes. The possible solutions when the mode is switched are divided into two parts, one is selected from the optimal solution obtained during the execution of the compact algorithm, and the other is generated using a uniform distribution, as shown in Algorithm 2, where n is the number of new solutions generated per iteration after switching.
There are many ways to obtain the optimal solution from the operation of the compact algorithm. This article chooses the key solution of the optimal solution in the previous iterative process.
The selection of the key solution needs to conform to Equation (7); the difference between the fitness function value of the key solution and the previous solution is greater than the difference of the first m optimal values of the key solution. m in this paper is 20. t represents the current number of iterations and best f it is used to store the optimal solution obtained during each iteration. By selecting the key solution from the optimal solution for each iteration, it is possible to use the previous search results for a more refined search, which is a memory-based approach. Selecting those breakthrough solutions in the iterative process through Equation (7) can assist in fine search after switching. Based on the above introduction, the flow chart of the icCS algorithm in this paper is given in Figure 2.

Experimental Results
The proposed algorithm was tested. The test function used CEC'17 benchmark suite [45]. The 28 test functions used in this study include unimodal functions, simple multimodal functions, mixed functions, and composition functions. All test functions used are minimization problems and are defined as follows: where D is the number of dimensions and the search range is [−100, 100] D . According to the introduction of CEC'17 benchmark suite, f 2 was excluded because it exhibits unstable behavior, especially for higher dimensions in test functions. Compared with the same algorithm implemented in Matlab, the performance of the one implemented in C is very different [45]. Thus, 28 test functions were used to the the algorithm in this paper. All tested algorithms maintained consistent parameter settings. The population size of all algorithms was 20 and the number of algorithm iterations was set to 3000. Each algorithm was tested five times on each function and the average value was retained. The parameter settings of each comparison algorithm are shown in Table 1.

Comparison with Common Optimization Algorithms
The improved compact cuckoo search algorithm proposed in this paper was compared with common classical algorithms on the test functions: the original CS algorithm [5]; the Adaptive Cuckoo Search Algorithm (ACS) [46], in which the parameter p a was set to 0.25; common PSO [47]; DE [48]; and the sine cosine algorithm (SCA) proposed in 2016 [49]. The comparison results are shown in Table 2.  Table 2 shows the average value obtained by running the icCS algorithm and other algorithms on the test functions. The last row in the table summarizes the comparison results of icCS algorithm and other algorithms, where w indicates on how many test functions icCS has achieved better results than the algorithm results of the current column. Table 3 shows the standard deviation of the icCS algorithm and other algorithms on the test functions.
According to the data in Tables 2 and 3, the algorithm proposed in this paper achieved better results than other algorithms on the test functions. Especially on specific functions, such as f 1 , f 12 , and f 13 , compared with CS and ACS algorithms, the proposed algorithm could obtain better and more stable results. At the same time, the overall performance of each algorithm compared with the icCS algorithm was measured at a significant level α = 0.05 under the Wilcoxon's sign rank test (Table 4) [50].
According to Table 2 Table 3 gives the corresponding data. Combined with the data in Table 2, the icCS algorithm proposed in this paper has similar stability compared with CS and ACS algorithms. However, the CS and ACS algorithms on f 1 , f 12 , and f 13 did not achieve good results. Based on the above comparison, the overall performance of the algorithm icCS proposed in this paper is better on 28 test functions.

Comparison with Compact Algorithms
Tables 5 and 6 compare the proposed pcCS algorithm with other common algorithms using the compact method, including compact Particle Swarm Optimization (cPSO) [12], compact Bat Algorithm (cBA) [15], and compact Artificial Bee Colony algorithms (cABC) [51]. The number of virtual populations was set to 20 and the parameters of the algorithm remained the same as those in the original document.
This paper compares the proposed icCS algorithm with other compact algorithms in 10D and 30D optimization. At the same time, the overall performance of each other algorithm was measured at a significant level α = 0.05 under Wilcoxon sign rank test. According to the data in Tables 5 and 6, the algorithm proposed in this paper has better performance than the other three compact algorithms and can obtain better results. For the cBA algorithm in Table 5, icCS achieved better results on f 1 , f 3 , f 4 , f 12 , f 13 , f 18 , f 19 , and f 29 . Combined with the results of Wilcoxon sign rank test, the proposed icCS algorithm was significantly better than the cBA algorithm on 28 test functions. For the cPSO and cABC algorithms, the cABC algorithm could still obtain better results when it was optimized in 10D, but, when it was optimized in 30D, as shown in Table 6, the cABC algorithm was not as stable as the proposed icCS algorithm. As shown in Table 5 for 10D optimization and Table 6 for 30D optimization, the performance of the proposed icCS algorithm in different dimensions is similar and does not fluctuate too much. According to the results of the Wilcoxon sign rank test, the proposed icCS algorithm was significantly better than other algorithms using only compact technology for the 28 test functions and both 10D and 30D optimization.

Convergence Evaluation
The optimal value obtained by the algorithm cannot completely define the validity of the algorithm's search principle. It is also necessary to evaluate the convergence of the algorithm to measure the speed of the algorithm reaching the optimal value. In this study, two unimodal functions ( f 1 , f 3 ), two simple multimodal functions ( f 6 , f 10 ), two hybrid functions ( f 12 , f 13 ), and two composition functions ( f 22 , f 28 ) were selected as the test functions to compare the convergence of icCS and other common classic algorithms for evaluation of convergence. The comparison of the convergence performance of the icCS algorithm proposed in this paper and other common classical algorithms is shown in Figures 3 and 4. Because the algorithm proposed in this paper combines compact-and population-based technologies, the overall complexity of the algorithm is higher than that of algorithms using only compact. Based on the introduction of the algorithm in Section 3, the proposed icCS algorithm is divided into two phases. The first stage uses compact technology. To increase the global search capability at this stage, a step of uniform sampling is added in this paper. Sn additional uniform distribution sampling is performed on the basis of compact using normal distribution sampling. In this way, a new solution is generated during each iteration and two new solutions are generated, which increases the global search capability and also increases the complexity of the algorithm. At the same time, because the compact method generates fewer solutions, as shown in Figures 3 and 4, the early convergence speed of the proposed algorithm is slow.
After the algorithm switches to the second stage, the algorithm uses a population-based method for enhanced search in order to jump out of the local optimum. The algorithm complexity at this time is the same as the original population-based algorithm. In addition, during the execution of the first phase of the algorithm, it is necessary to prepare for switching to the second phase. The key solutions in the first phase need to be saved, and it is necessary to judge whether to switch to the second phase continuously. Therefore, the overall complexity of the algorithm is similar to or slightly higher than the original algorithm.

Application to Drone Logistics Hub Location
The location of the drone logistics hub is briefly introduced in Section 2.2, which establishes a simple model based on three influencing factors, and then determines the fitness function of the model. In this section, the proposed algorithm is applied to the model for testing.
In fact, there are many studies on the way of drone logistics. The endurance time and load capacity of the drone itself also limit the development of drone logistics. However, there are studies on the innovative design of drone applications in the logistics industry [25]. With the development of technology, the restrictions on drone logistics due to the lack of performance of the drone itself will be gradually resolved. Thus, this paper focuses on the logistics issues in rural areas and remote mountain areas, and uses a model of logistics hubs and drones. A certain number of unmanned logistics hubs is used to provide logistics distribution services for surrounding villages and drones complete the end logistics tasks.
According to the above model and the introduction in Section 2.2, this article considers three factors that affect the location of the logistics center: the distance from the village to its logistics hub, the rural population, and the degree of transportation difficulty from the logistics hub to the village. The significance of the first factor is that the total distance between the logistics hub and the villages it serves is the smallest, and its operating costs are also smaller. The significance of the second factor is that, if the rural population is larger, the frequency of services required is higher, thus the proportion of the village in the whole is higher. Then, the logistics hub needs to be closer to the village, thus the cost is lower and the logistics efficiency will be higher. The significance of the third factor lies in the advantage of the drone's straight flight. Traditional land logistics methods need to consider terrain factors, and roads are not straight, thus logistics in remote areas or mountain regions is more difficult. By adding this factor, logistics hubs can provide better logistics services to areas with difficult transportation. Based on the above and the introduction in Section 2.2, the objective function used in this paper is written as where k is the kth village, cp k is the population of villages k, N is the total number of villages, R k is the radius of the village, and H k is the straight line distance from the village to the nearest logistics hub to the village. The meaning of L2 k is the same as H k , and L1 k is the land transportation distance from the current village to the nearest logistics hub. The goal of the intelligent algorithm is to find the best logistics hub location so that the objective function is the smallest overall. That is, H k is minimized in Equation (10) by an intelligent algorithm to achieve the overall minimum, where d j is the position of the drone logistics hub in a certain dimension.
A program was used to generate the original test data based on the proposed drone logistics hub location model. Thirty random village locations were generated in a two-dimensional space of 50,000 m × 50,000 m. The radii of the villages were 200-900 m and their populations were 300-3000. The degree of traffic difficulty was the land transportation distance divided by the drone's straight flight distance, which ranged from 1 to 3. Two generated models were used for testing. Table 7 shows the results of testing using Model 1. N is the number of logistics hubs for 30 villages. Each test was executed 50 times and the number of iterations was 3000. Table 8 shows the data results of the test using Model 2. N is the number of logistics hubs for 30 villages. Each test was performed 30 times and the number of iterations was 5000.   Figure 5 shows the results of running different models using different algorithms, where circles represent the village location, squares represent the calculated logistics hub location, and circles of different sizes represent villages with different radii. According to the execution result data, setting more logistics hubs can obtain smaller fitness function values. However, the construction of the logistics hub itself also requires costs. The larger is the number of logistics hubs, the higher is the overall cost, and the more dispersed are the goods, thus it is necessary to set an appropriate number of logistics hubs based on actual needs. It can be seen in Figure 5 that the location of some logistics hubs has been transferred to the village area after calculation, which means that the cost of logistics hubs will also be reduced, thus they can be selected based on actual conditions.

Conclusions and Discussion
Drone logistics will play an increasingly important role in the logistics industry with the increase in the degree of automation of the supply chain. This paper presents a simple location model for a drone logistics hub. This model considers three factors that affect location selection and determines the fitness function of the model. This paper is based on the original cuckoo search algorithm, which is improved by compact and other technology, and proposes the icCS algorithm. On the basis of sampling using the normal distribution, uniform distribution sampling and optimal solution perturbation are added, and, for the problem that is easy to fall into a local optimum, the global search ability is improved by increasing the number of generated solutions. Then, this paper uses the proposed algorithm to calculate the location for drone logistics hub. Compared with other algorithms, it can get better execution results. However, the model proposed in this paper is still inadequate, the influencing factors included are not comprehensive enough, and further improvements can be made, such as adding logistics hub cost, topographical influence, path planning between logistics hubs, and communication and control between logistics hub and drone. The proposed approach may be further improved by adopting some intelligent and efficient algorithms.


Computer-Mediated Advertising as a Correlate of Buying Behavior Among Youths From South-East Nigeria

This study examined the correlation between exposure to computer-mediated adverts and the buying behavior of youths from Enugu State. The correlational survey was used for the study, while a sample of 385 was selected through a multistage sampling technique. In the analysis of the result, simple percentages were used to achieve the research objectives, while the Pearson correlation coefficient (r) was used to test the hypotheses raised. The result showed a strong positive correlation between the engagement in computer-mediated communication (CMC) and exposure to computer-mediated adverts (r = .815, n = 362, p < 005). The findings also showed a strong negative correlation between the format of computer-mediated advertising (CMA) and the duration of viewing (r = −.241, n = 362). Finally, the researcher found a strong positive correlation between exposure to CMA and buying decision (r = −.666, n = 362, p < 005). The researcher concludes that the level of engagement in CMA correlates exposure and eventual purchase likelihood. The researcher recommends, among others, that efforts aimed at reaching youths through CMC should also incorporate their level of engagement.

interactivity, and computer intelligence allow advertisers to expand the boundaries of advertising beyond brand awareness and exposure. Although some scholars (e.g., Bahr, & Ford, 2011;Dehkordi et al., 2012;Fagerstrøm & Ghinea, 2010) refer to CMA as e-marketing, the crux of the matter is that the emergence of the internet has resulted to changes in advertising. Luk et al. (2002) posit that CMA helps to market products and services through interactive and colorful catalogs and provides the audience with current and available information. According to the trio, such advertising also allows the audience to make both local and international purchases as there are numerous websites designed to promote sales and to maintain relationships with customers. Zheng and Yeqing (2002) hold that CMA is less annoying than usual advertising.
The overall goal of CMA is to communicate products qualities to the target consumers and eventually influence their buying behavior. This implies that the essence of CMA 938701S GOXXX10.1177/2158244020938701SAGE OpenAsogwa research-article20202020 1 Federal University Oye-Ekiti, Nigeria is to promote marketing of products. Todorova (2015) posits that marketing communications represent the voice of the company and its brands-they are the means by which the company can establish a dialogue and build a relationship. Fill and Jamieson (2006) corroborates that all organizations, irrespective of size, commercial, government, charities, educational and other not-for-profit organizations, need to communicate with a range of stakeholders.
Knowledge of the buying behavior of consumers is an ever-interesting area in advertising because marketers are usually interested in explaining and predicting consumer behavior. Munthiu (2009) avers that the decision of purchasing an item does not immediately trigger motivation, perception, learning, memory, personality, and attitude are fundamental drivers in the unfolding of the decision process that presupposes the consumer's covering of five stages: problem recognition, information search, evaluation of alternatives, purchase decision, and postpurchase behavior. Although many factors such as income level, education level, gender, location, among others, have been identified as essential to buying behavior, age is said to play a critical role in deciding what to buy. Evidence in the literature (e.g., Khan & Chawla, 2015;Singh & Dalal, 1999) points to the fact that age is a pivotal variable that determines buying decision. Also, there is empirical evidence suggesting that computermediated communication is most common among the youth. For example, the Dunahee and Lebo (2016) reported that at least 90% of respondents ages 18 to 24 years engage in computer-mediated communication daily. In Nigeria, youth are people between the ages of 18 and 35 years. This is contained in the National Youth Policy and Strategic Plan of Action of the Federal Government of the Federal Republic of Nigeria (2001) as cited by Gever (2015). Therefore, this study adopted the theory of reasoned action to examine the correlation between CMA and buying behavior of youths from Enugu State.

The Problem
Although computer-mediated communication is an attractive area for 21st-century scholars, studies on CMA are still emerging. Much of the literature on advertising has focused on conventional media like radio, TV, newspaper, and magazine. Studies (e.g., Benek et al., 2011;S. Kumar, 2013) have also shown that youth and children influence family buying decisions. This implies that knowledge of the relationship between exposure to CMA and buying decision of youth could also offer an insight into buying decisions of the family. Khan and Roni (2013) corroborate that the youth market is one of the most appealing and attractive markets because they are considered to have more pull (power) in their crucial family decisions and purchases. There is also evidence suggesting that people of young age take part in computer-mediated communication most, hence are likely to be exposed to computer-mediated adverts. Although it may be tempting to conclude that most youths are exposed to computer-mediated adverts because they are engaged in computer-mediated communication, such an assumption may lack empirical proof. Advertisers are aware of youth technology culture and have taken advantage of it. Moreno (2018) notes that youth are key stakeholders in advertising. This makes it essential to understand the relationship between computer-mediated adverts exposure and eventual purchase likelihood.

Objectives of the Study
The general objective of this study is to determine the relationship between computer-mediated adverts and the buying decision of youth from Enugu State. Specifically, the researcher sought to achieve the following: 1. To ascertain the relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. 2. To discover the relationship between format of computer-mediated advert and estimated viewing duration. 3. To examine the relationship between exposure to computer-mediated adverts and buying behavior.

Research Hypotheses
This study tested the following hypotheses: Hypothesis 1: There is a significant statistical relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. Hypothesis 2: There is a significant statistical relationship between the format of the computer-mediated advert and estimated viewing duration. Hypothesis 3: There is a significant statistical relationship between exposure to computer-mediated adverts and buying behavior.

Computer-Mediated Adverts Format
As stated earlier, CMA describes messages about products or services which are made available to the receivers through new communication technologies. December (1996) says that it is referred to a situation in which commercial messages are created, exchanged, and perceived through networked telecommunications systems that facilitate encoding, transmitting, and decoding messages. Deshwal (2016) describes CMA as a type of mass communication which is based on the traditional form of advertising but develops its communication strategies in correlation with the new technical and medium-based requirements. CMA could reach the receivers through different mediated devices like the laptop computer, the desktop, mobile phone, an iPad, a tablet, among other devices that posses the ability to process, store, and retrieve messages. Computer-mediated adverts may appear in different formats like video which shows the features of the product and draw people in with sound and motion. The format could also be in the form of the image which guides people to the destination of the websites or applications through high-quality visuals. Farace et al. (2020) in their study found that the visual component is essential in stimulating purchase. Interestingly, computer-mediated advertisements include visual and motion formats. The format could equally be regarding collection which encourages shopping by displaying items from products catalog. Also, computermediated adverts could be informed of the carousel which reveals up to 10 images or videos within a single advert with each having its individual like. There is also slideshow format which uses motion, sound, and text to tell the story about the advert on connection speed. V. Kumar et al. (2017) add that computer-media advertising is now critical in 21st-century marketing. Appiah (2006) reported that computer-mediated communication users were more likely to have confidence that a site was targeting them, regard a site more positively, and rate the product more favorably when the site has audio/video testimonials than they were when the site is made up of either text/picture testimonials or no testimonials. Appiah's study implies that video format was most effective in influencing buying behavior. Germelmann et al. (2020) in their study reported that advertising medium is essential in determining advertising effectiveness. Their result suggests that computer-mediated adverts may play a role in consumer behavior.

Youth and Buying Behavior
The buying behavior of youth is an interesting area because of the influence they exact in the buying decision of families. Khan and Roni (2013) found that youth market is one of the sought-after markets because they are regarded to have more influence on their main family buying decisions. Therefore, a critical center of firm's marketing actions is toward these young consumers, and they place more attention on the determinants of buying behavior and brand choice of their obsession with new technologies. Chandwani et al. (2015) reveal 10 major steps (under pre-, intra-, and postpurchase behavior) identified for youth while purchasing. According to Chandwani et al., these factors include budget analysis; brand preferences or brand loyalty; usage or purpose, or requirement; specifications of the product; products available; products or brands comparison; product availability in stores; final purchase; consumption; satisfaction or dissatisfaction. Khan and Roni (2013) hold that today's youths are positively disposed to technology. Khan and Roni add that as a result of youth's fast adoption curve and orientation toward technology and innovative feature, this age group has become an area of significant interest to the marketers. The assertion of Khan and Roni is critical to the current study because it has shown that new communication technologies are common among youth, thus making it appropriate to investigate the correlation between exposure to computer-mediated adverts and buying behavior. Literature focusing on new media and advertising abound. Kalia and Ashutosh (2016) did a study on effects of online advertising on consumers and found that although different types of internet advertisements appear on the website, respondents express preference rectangular banner advertisements and skyscraper ads which are in vertical format.
Mohammed and Alkubise (2012) investigated the influence of online adverts on a sample in Jordan. The results revealed that internet skills, income, internet usage per day, the content of advertisement, and the location advertisement are essential factors that impact on the effectiveness of an online advertisement. However, two notable findings emerged: The first was the critical considerable role of website language and the second and maybe most importantly was the impact of other people opinions on the effectiveness of an online advertisement. Mathew et al. (2013) investigated the influence of web advertising on consumers in Maiduguri, Metropolis. The study discovered that a majority (100 [71.94%]) of the respondents said their disposition toward web advertising was positive. A minority (39 [28.06%]) of the respondents said that their disposition toward web advertising was negative. A total of 102 (73.38%) respondents said their attitude toward web advertising was informative. The study also found that a majority (42 [30.22%]) of the respondents said web advertising influences them to use some of the products and services. Afzal and Khan (2015) did a study on the effect of mediated and conventional advertisement on consumer buying behavior of branded garments. It was reported that the content of the advertisement, design, quality, previous buying experience of the consumer, and the loyalty of consumer toward the brand are critical factors that influence consumer buying behavior and affect the direct impact of online and conventional advertisement on consumer buying behavior through their strong mediating effect.
Aday and Yener (2014) investigated many factors that might influence the young consumer's behavior at the point of sale. The researchers revealed those factors, namely, packaging, labels, production, best before dates, and ingredients, among others.
Hayta (2013) did a study to know the influence of social media on the buying behavior of youth in Turkey and found that social media tools create a statistically significant difference on the purchasing behavior of consumers according to their age groups and educational status. This is because Hayta found that participant attitudes toward buying behaviors and social media relations cause a significant difference in educational level, t(686) = 6.666, p > .01. Fatima and Lodhi (2015) studied the impact of advertisement on buying behaviors of the consumers in Pakistan. The results showed that advertisement is very useful in creating the awareness among the people, but they are failed to build strong perceptions in the mind of consumers. Both of these variables such as consumer awareness and consumer perceptions will motivate the consumer to buy a particular product, as there is a positive relationship present in between them.
Van Berlo et al. (2020) in a study reported that familiarity with brand significantly moderates the impact that adolescents playing advergames has on their ability to recognize the commercial aim of advergames. Their result also revealed that smartphone attachment triggers recognition of the commercial objective of advergames among the sample examined. Schnack et al. (2020) conducted a study to ascertain to determine shopping behavior of consumers with the utilization of 153 different categories of shopping trips. The researchers made use of observation research approach and the result showed that shopping behavior of consumers was determined by virtual stimulation. Devereux et al. (2020) did a study to examine the features of social media posts from small from that stimulate engagement from the consumers. The researchers conducted the study in Australia. Their social media posting of companies reveal their value of their online activities. The results of the researchers also revealed that the consumers were more interested in engaging with Facebook posts of companies than any other social media platform.
From the studies reviewed, it can be seen that the concept of CMA has not received substantial attention in the literature. Rather, most of the previous studies focused on online advertising, which is just one aspect of CMA because even mobile phone advertising is part of CMA. And mobile phone advertising does not necessarily make use of the internet, thus not part of online advertising. Also, adverts in video games are also part of CMA but not part of online advertising. Therefore, CMA is broader in scope.

Theoretical Framework
This study found expression on the theory of planned behavior. Ajzen postulated the theory in 1986. The fundamental postulation of the theory is to explain human behavior. According to the theory, individual's intention to carry out an action at anytime is determined by the intention that the person has in mind. Behavior intention determined by three factors, namely, an individual's attitude toward behavior, subjective norms, and perceived behavioral control (PBC; Ajzen, 1991). In the views of Ajzen (1985), intention is "a person's readiness to perform a given behavior." Attitude defines the evaluation of a person concerning a behavior which can be positive or negative. subjective norms describe the opinion that a person's role model have about an issue. On its parts, PBC explains how less demanding or challenging it is for a person to engage in an action. Theory of planned behavior is considered useful as a framework for studies related to advertising. Zhang et al. (2018) made use of the theory to examine how young people in China react to green advert messages. Their results showed that the theory is an appropriate framework for examining issues related to adverting. Therefore, the researcher made use of the theory to explain the influence of computer-mediated adverts on youth in South-East Nigeria.

Method
The design that was used in this study was correlational survey. The design was deemed most suitable because it helped the researcher to determine the relationship between exposure to computer-mediated adverts and buying behavior of youth. The population of this was made up of all the youths from Enugu State aged 18 to 35 years. According to the National Bureau of statistics (2012), the total number of youth from Enugu State is 1,300,664.
The sample size of this study was made up of 385 youth. This was determined using the Australian calculator as provided by the National Statistical Service (NNS). The confidence level was 95% precision level of 0.05, and estimated variance of 5% was used. The researcher adopted the multistage sampling technique for this study.
First, the researcher considered the three senatorial zones in Enugu State as clusters. They are Enugu East, Enugu West, and Enugu North. At this stage, the researcher used purposive sampling to select one local government from each of the senatorial zones. Awgu from Enugu West, Nsukka from Enugu North, and Udi from Enugu East were selected. To sample the individual respondents, the researcher adopted simple random sampling by visiting the local government headquarters of the selected local government areas. Only those within the age bracket of 18 to 35 years were selected. Such persons also reported they were new media users. The questionnaire was used as the instrument of data collection. The reliability of the questionnaire was determined through a test-retest approach. To do this, initial copies of the questionnaire were administered to 20 persons in Nsukka; after 2 weeks, the same questionnaire was administered to the same respondents. The Guttman scale of coefficient of reproducibility was used to measure reliability of consistence of the instrument as shown below: . .
The calculation yielded 0.85 (85%), which was considered very high. The analyses were done using correlational analyses. In doing so, the Statistical Package for Social Sciences (SPSS 22. version) was used. The results were presented in tables.

Results
A total of 385 copies of the questionnaire were administered to the respondents, but only 362 copies representing 94% were retrieved and found useful. The sample was 52% male and 48% female. Also, average mean number of years that the respondents had been engaging in computer-mediated communication was 8 (range = 4-12 years). The device most commonly used for computer-mediated communication was the smartphone (95%). The frequency of engagement in computer-mediated communication was daily for most (82%) of the respondents. The motivation for was as follows: information exchange (83%), entertainment (67%), education (54%), and avoidance of boredom (41%). Overall, the respondents were asked to rate the level of on a trio of high level, medium level, and low level, and the result showed that most (72%) reported high level, 16% reported medium level, and 12% reported low level. Table 1 shows the result of the correlation between engagement in computer-mediated communication and exposure to computermediated adverts.
The result from the table above suggests that respondents who reported high-level engagement in CMC also reported full exposure to CMA. Also, respondents who reported lowlevel engagement in CMC also reported no exposure to CMA while medium-level engagement respondents reported glancing at CMA. Table 2 showed the cross tabulation between format of CMA and viewing duration. The result from the table above suggests that most of the respondents view CMA from image format and they do so within 0 to 5 min. Cumulatively, more than half of the respondents view the image format of CMA, followed by video and text. Table 3 shows the cross tabulation between Exposure to CMA and buying behaviour. The result from the table above revealed that most of the respondents who reported full exposure to CMA also reported that it influences their buying behavior. This is followed by those who reported glancing at such advert. Overall, of 64.1% of respondents who reported

Test of Hypotheses
The following hypotheses have been tested in this study: Hypothesis 1: There is no significant statistical relationship between engagement in computer-mediated communication and exposure to computer-mediated adverts among youths from Enugu State. Table 4 shows cross tabulation between engagement in computer-mediated communication and exposure to computer-mediated adverts. The result from the table above measured the relationship between the level of engagement in computer-mediated communication and exposure to computer-mediated advert using Pearson correlation coefficient. Preliminary analysis was performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong positive correlation between the two variables, r = .815, n = 362, p < 005, with a high level of engagement in CMC associated with exposure to CMA. Therefore, the first null hypothesis is rejected, and the researcher concludes that there is a significant statistical relationship between engagement in CMC and exposure to CMA among youths.

Hypothesis 2:
There is no significant statistical relationship between format of computer-mediated advert and estimated viewing duration. Table 5 shows correlation between format of computermediated advert and estimated viewing duration. The result from the table above measured the relationship between the format of the computer-mediated advert and estimated duration of exposure using Pearson correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong negative correlation between the two variables, r = −.241, n = 362, p < 005. This implies that as the CMA format changes, it negatively affects the duration of exposure. Therefore, the second null hypothesis is rejected and the researcher concludes that there is no significant statistical relationship between the format of the computer-mediated advert and estimated viewing duration.

Hypothesis 3:
There is no significant statistical relationship between exposure to computer-mediated adverts and buying behavior. Table 6 shows the relationship between exposure to computer-mediated adverts and buying behaviour. The result from the table above measured the relationship between exposure to CMA and buying behavior using Pearson correlation coefficient. Preliminary analyses were performed to ensure no violation of the assumptions of normality, linearity, and homoscedasticity. There was a strong positive correlation between the two variables, r = −.666,  -tailed) .000 N 362 362 Note. CMA = computer-mediated advertising. **Correlation is significant at the .01 level (one-tailed).  n = 362, p < 005. This implies that exposure to CMA positively affects buying behavior. Therefore, the third null hypothesis is rejected, and the researcher concludes that there is no significant statistical relationship between exposure to computer-mediated adverts and buying behavior.

Discussion of Findings
This study investigated exposure to computer-mediated advert through computer-mediated communication and the buying decision of youth from Enugu State, Nigeria. The result of this study showed respondents who reported highlevel engagement in CMC also reported full exposure to CMA. The result of the hypothesis tested also showed a strong positive correlation between engagement in CMC and exposure to CMA (see Tables 1 and 4). The result of this study is consistent with that of Kalia and Ashutosh (2016). Also, the result of this study showed that the most preferred CMA format was the image format and this is viewed for 0 to 5 min. The result of the hypothesis testing showed a strong negative correlation between CMA format and viewing duration. This implies that as the format changes, the view duration also changes. Overall, the result showed a significant correlation between the format of CMA and viewing duration. This result is contrary to the study of Giordano et al. (2015). Finally, the result of this study showed that most of the respondents who reported high engagement in CMC also reported that it correlates their buying decision. The result of the hypothesis testing also showed a strong positive correlation between both variables. This finding is consistent with previous studies (e.g., Aday & Yener, 2014;Fatima & Lodhi, 2015;Hayta, 2013) focusing on CMC and buying behavior. This result has revealed two broad implications. First, it has shown that the level of engagement in CMC may not necessarily be the same among all youths as may be assumed. While some youths are likely to be highly engaged in CMC, others may be moderately involved. Such level of involvement has implications for behavior change.
Therefore, the relevance of this result is beyond advertisers as other groups like political parties, change agents, social workers, media practitioners, and so on wishing to plan and implement behavior change communication through CMC could find the result of this study beneficial. Also, Scholars from journalism and media studies could also leverage on the result of this study for the purposes of understanding the interface between the level of engagement in CMC and behavior change. Theoretically, this result has implications on the theory of planned action. The underlying assumption of the theory is that consumers act on a behavior based on their intention to create or receive a particular outcome. Hence, the result showed that higher engagement in CMC correlates exposure to CMA and eventual purchase likelihood; it can be argued that those youths who are engaged in CMC do so to achieve particular objectives and information on products could be part of it. This is more so that the result of this study showed that information is top on the motivation for engagement in CMC.

Conclusion
This study has shown the correlation between CMA and buying decision of youths in Enugu State. The result proves that the level of engagement in CMC is an essential consideration in understanding the exposure to CMA and ultimately purchases likelihood. This study has practical and scholarly contributions. Practically, the result of this study has shown that knowledge of the motivation for engagement in CMC as well as the level of engagement is cardinal for reaching 21st-century youth via CMC. Therefore, anybody or groups of persons who are interested in reaching youth via CMC or even understanding their engagement behavior must pay close attention to the level of engagement. Therefore, advertisers, political parties, health workers, and journalists could find this information beneficial. Scholarly, this result has added to the body of knowledge on youth participation in CMC. The study has also expanded literature in the study of advertising and purchase likelihood. Based on the result of this study, the research recommends as follows: Campaigns aimed at understanding and reaching the youth via CMC should pay close attention to their level of engagement in CMC. Advertisers should use more of image format as doing this may lead to longer duration of viewership. Finally, the message should be created in a manner that it can be effectively understood between 0 and 5 min of viewing.

Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding
The author(s) received no financial support for the research, authorship, and/or publication of this article.  -tailed) .000 N 362 362 Note. CMA = computer-mediated advertising. **Correlation is significant at .05 level of significance.


Study on the Employability of International Business Graduates

How to improve the vocational skills of international business graduates has become a thorny issue in universities in the context of rising trade protectionism. By comparing and analyzing the training programs of international business professionals from 36 universities in China, the study summarizes the employability of international business graduates, which contains five aspects: international business skills, basic competencies in international business, professional comprehensive quality, awareness of improving self-competence, innovation capability of international business. Based on the current situation of international business professional education, the study puts forward four measures to enhance the employability of international business graduates: Relying on the Foreign Trade Park to build an integrated international business personnel training system of PSEUR (policy, student, enterprise, university, research institution); Subdivide the employable capabilities of international business graduates; Make full use of the emerging information technologies to improve the efficiency of international business graduate employability training; Optimize the curriculum of international business major and improve the efficiency in teaching. These recommendations will contribute to the improvement of the University's international business talent development program.

I. INTRODUCTION
Recently, although international free trade has been challenged by artificial trade frictions, trade between countries along the route is becoming more frequently in the context of the Belt and Road Initiative. It is vital to enhance the employability of international business graduates. Because the economic driving force of resources seeking optimal allocation remains unchanged, the development of international trade markets is unstoppable. Facing the volatile international business environment, international trade practitioners (international business graduates) must be equipped with higher professional skills and qualities. The massive expansion of higher education in China has led to questions about the quality of graduates in the labor market and their ability to meet employers' requirements [1]. Therefore, although foreign trade-oriented enterprises are very short of staff, there are still a large number of international business graduates unemployed The practical significance of studying employable ability lies in improving the efficiency of human resources training.
As the demand for talent-to-hire capacity in different industries always change at any time, the general talent ability analysis method cannot meet the requirements of professional human resources management. We can effectively analyze the actual needs of the employable capacity system by combining with industry-specific human resources employable capacity requirements standards. As a national and social talent training institution, colleges and universities play a dominant role in cultivating college students' employability. The knowledge, skills, and conducts that students receive during school are largely influenced by the characteristics of a university and the system of training talents [2]. Therefore, the employability of graduates will be determined by the scientific and reasonable talent training program in colleges and universities. This study collects and analyzes the talent training programs of international business in 36 Chinese universities, combines similar items, summarizes the competence training content accepted by Chinese international business graduates, and refines the employable ability of Chinese international business graduates from the perspective of talent supply.

II. THEORETICAL REVIEW
Research on employability was launched at the beginning of the 20th century in Britain, where the industrial revolution was booming. The British scholar Beveridge proposed the "employability" and "employable" in 1909. Beveridge attributed unemployment to the employability of the workforce not to meet working standards [3]. The study of employability has gone through the process of "definition interpretation, system construction and practical". As a matter of fact, employability is a set of achievements of skills, understandings and personal attributes-that make graduates more likely to gain employment and be successful in their chosen occupations, which benefits themselves, the workforce, the community and the economy [4]. Three significant themes emerged out of the past research, each one focusing on different components of graduate employability: Business Specific Issues (business, related knowledge and skills), Interpersonal Competencies, Work Experience and Work, Based Learning [5]. The previous studies have focused on explaining what employability is and how to measure it, and rarely looking at how to improve a labor's employability. Based on cognitive and social psychology, Peter T Knight & Mant Z Yorke co-authored the USEM employment theory model: professional understanding *Corresponding author (knowledge), skills (including key skills), self-efficacy (including the sense of self-development), meta-cognitive (including the ability to learn how to learn) [6].
The researchers have put forward different solutions to analyze and explain employability. But most of them are normative analysis based on individual subjective empirical judgment and the conclusion is generally what graduates should or should not do. Although individual employability can be obtained from multiple platforms, university professional education is the main source for international business graduates. Independent competence and sound personality are two equally important goals in the talents cultivation in universities. In essence, the employability is a "threshold" index system that measures the value of human resources and reflects the employer's minimum requirements.

III. WHAT INTERNATIONAL BUSINESS GRADUATES HAVE
LEARNED?
According to 2018 statistics, a total of 149 undergraduate colleges and universities opened international business majors in China. In order to obtain the content of international business students, the study collects the international business professional training programs of 36 colleges and universities, compares the specific content, analyzes the ability of talent training goals and talent specification requirements then summarizes the educational content received by international business students in Chinese universities. As the main source of labor market talent is university graduates, the educational content received by international business students is equivalent to their employability.
At the same time, colleges and universities take serving the local regional economic and social development as their mission, then the talent specification standards in their talent training programs are closely related to the regional economic structure. In spite of this, international business graduates must have common professional skills in the integrated market. By comparing and analyzing the international business professional training programs of 36 colleges and universities and merging the similar items, the study summarizes the content of the employable ability of international business graduates, which includes 29 items (see Table I).
Not all 29 items of competence in the table I are included in every talent development programs of the 36 colleges and universities, for example, some colleges and universities do not require students to "develop their own potential and constantly pursue progress". In the table I, the number refers to the times that competence items appear in 36 talent development programs, and frequency refers to the proportion of this competence item in all competence requirements. Most papers try to split employability into several categories before defining what is included in the term. Employability can be split as skills and knowledge, without the personal aspect [7]. Some skills are more commonly cited than others, like communication, team working, information technology and planning and organizing. The personal attributes that occur most often in research on employment include flexibility, adaptability, hardworking, commitment and dedication [8]. The research value of employable ability lies in improving the matching degree of professional supply and demand by analyzing the needs of both supply and demand in specific industries. To answer the question from the title more accurately, a survey of human resource managers, foreign trade business executives and foreign-related market business practitioners in foreign trade-oriented companies was designed for this study. The questionnaire consists of 30 questions which are converted from 29 items in Table І and the last question is "please score the usefulness of what you have learned to your work". The answer is using the Likert scale (based on a 5-point Likert scale), which uses the numbers "1-5" to refer to "Totally inconsistent", "Inconsistent", "Indecisive", "Consistent" and "Totally consistent". A total of 420 questionnaires were distributed and 403 questionnaires were recovered, with an effective rate of 95.95%.

A. What is the employability structure of international business graduates?
Based on the questionnaire data, this study adopts Exploratory Factor Analysis to explore the employability structure of international business graduates. As shown in the table II, the KMO statistic is .887>0.7, and the effect of factor analysis is relatively good. The Bartlett spherical test shows that the independence hypothesis of each variable is not valid, so the applicability test of factor analysis is passed. Through principal component analyzing, I take the eigenvalue>1 as the initial factors then 5 factors are extracted. The explanatory power of 5 factors is 54.631% so the factor analysis effect is acceptable. In order to reflect the attribution relationship between original variables, the data structure is simplified after matrix rotation converged in 6 iterations (table  III).
By comparing the contents of the items that are converged by the 5 factors, the study summarizes the five components of the employability of international business graduates (table IV): (1) Professional comprehensive quality; It specifically refers to personal character and work ethic, common sense and manners of business etiquette, professional loyalty etc. (2) Basic capability in international business; It is mainly the ability to use foreign languages for business activities, mastering and applying the laws and regulations of international markets, cross-cultural communication, collaboration and organizational management capabilities etc. (3)International business skills; It includes customs declaration commodity inspection and customs clearance, international payment and settlement, management of bills and certificates etc. (4) Awareness of improving self-competence; It contains the awareness of developing your potentiality spontaneously, pursuing progress constantly, learning new knowledge and technologies actively and effectively etc. (5) Innovation capability of international business; It involves in exploring new ways of trade based on the Belt and Road Initiative, recognizing and apply new trade models based on cross-border e-commerce etc. These capabilities are designed to enable international business graduates to cope with the rapidly changing foreign trade market environment and target customer needs.

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The five components on the employability of international business graduates are extracted from the talent training programs of 36 universities in the perspective of talent supplying. Do these competencies acquired on campus meet the needs of specific work?

B. Are international business graduates qualified for specific jobs?
As shown in Table IV above, the 5 competencies´ mean (Mean C ( i ) ) are 2.63, 3.11, 2.07, 2.13, 2.25. The information reflects the practicality of the international business professional training program in colleges and universities. It also reflects the consistency between the teaching content designed by the talent training program and the competencies. Although the mean of each competency is not high, it is acceptable for Mean C(i)>2. But when it comes to how to evaluate the usefulness of the expertise you have learned in university; the average scores are only 1.20 (table IV). Since the minimum score is 1, it is a very low assessment and means that the international business education is almost useless for practical job requirements. Many respondents believe that international business graduates are barely able to do the actual job on their own, and worse off, they are reluctant to work hard.
Instead of mechanically engaging in cross-border business, international business graduates ought to seek ways to explore international markets and promote trade development. In view of this phenomenon, we must reflect on the practicality of international business professional education.

V. PROPOSALS TO ENHANCE THE EMPLOYABILITY OF INTERNATIONAL BUSINESS GRADUATES
At present, the training mode of international business majors in Chinese universities is "professional + foreign language + skills + entrepreneurial quality" and the goal of ability training is strengthening the professional foundation, broadening the field of knowledge, focusing on the application of knowledge and improving practical skills. This article explores how international business professionals can be fostered by the higher education institution. For the international business education of colleges and universities, two problems need to be solved: what expertise to teach and how to carry out professional teaching activities? The design of teaching and learning for employability needs to offer an experience for students which allows them to see their employability as part of their core activities in higher education.

A. Relying on the Foreign Trade Park to build an integrated international business personnel training system of PSEUR.
The PSEUR is an innovative and efficient talent training program. PSEUR means policy, student, enterprise, university, research institution. International trade must be guided by the relevant national policies, so practitioners can't change it only by adapting to it. Students are the link between universities, enterprise and research institutions. The main reason why enterprises cooperate with universities is that universities are the base of talent supply. In the process of cooperation between enterprises and research institutions, they not only realize the sharing of technology and information, but also share talents, and then jointly cultivate reserve talents. Therefore, universities should take the initiative to set up the PSEUR system and build an efficient platform for international business personnel training. It can give full play to the advantages of its own resources, fundamentally solve the problem of disconnect between school education and social demand, narrow the gap between the supply of university talents and the demand of social talents and enhance the ability of graduates to work. it is inappropriate to assume that students are highly employable on the basis of curricular provision alone: it may be a good harbinger but it is not an assurance of employability [9]. The

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demand of talent that can be employed in the international trade market is constantly changing. the PSEUR system can achieve the balance of employable ability in the dynamic process, so that the supply of talent capacity meets the demand of talent capacity.

B. Subdivide the employable capabilities of international business graduates
In fact, international commerce involves a wide range of business, which refers to the transnational business activities arising from the international trade and international investment. International trade includes goods, services and intellectual property transactions. The current hot-topic international investment mainly refers to international direct investment, including sole proprietorship, joint ventures and cooperative ventures. For students to be more specialized in a particular field of study, it is necessary to further segment the learning directions of international business, so as to improve their employability.

C. Make full use of the emerging information technologies to
improve the efficiency of international business students employability training Information technology can not only provide fast and timesensitive international market information, but also change the traditional teaching methods. Depending on the contents of Table І, the basic skills of international business graduates are customs declaration, commodity inspection and customs clearance, International payment and settlement, classification of import and export commodities and cross-border logistics, etc. These solidified business processes can be learned efficiently through the international business network information teaching platform. The prerequisite for international business innovation and practice is to know the real-time and effective international market information. Therefore, mastering network information technology will help to improve the employability of international business graduates.

D. Optimize the curriculum of international business major and improve teaching efficiency
For the international business courses content, building a teaching content system based on advantageous and characteristics industries will be able to enhance the employability of international business graduates more effectively, such as tea export trade, cross-border trade of flowers, etc. For the teaching methods, it is best to focus on practical teaching. Students undertaking work placements learn more from their placements if they reflect on their experience during their placement. Reflective practice is noted as a key capability in many professions [10]. The ultimate goal of optimizing professional curriculum is to enable students to do what they want to do in future.

VI. CONCLUSION
In the supply-side perspective, this paper summarizes 5 items of employability from the 36 international business professional talent training programs. Then through a questionnaire survey of international business practitioners, the paper examines that whether 5 items of employability match with the actual work requirements by analyzing of questionnaire survey data. Most respondents who are engaged in international business agree that the university's talent development program meets the specific job requirements, but don't believe that professional education in university is useful for actual work. In response to this situation, four measures are proposed to improve international business professional education. As a matter of factor, the issue of student engagement in employability is therefore manifold. It depends on the effectiveness of programmed design, implementation and delivery which in turn depends on support and agreement from both management and academic staff [11]. The position taken in this study is that employability goes well beyond the simplistic notion of key skills, and is evidenced in the application of a mix of personal qualities and beliefs, understandings, skillful practices and the ability to reflect productively on experience.
While it is inappropriate to assume that students are highly employable on the basis of university provision alone: it may be a good harbinger, but it is not an assurance of employability. Employability derives from the ways in which the student learns from his or her experiences [6]. To provide students with internship opportunities and practical platform, The PSEUR is an effective way to train international business professionals. In general, employability includes two dimensions: capacity structure and ability level. Only when the supply capacity structure is matched with the demand and the ability level is up to the demanded standard, can international business graduates be employed.