An application of extended elitist non dominated sorting Genetic Algorithm in multi objective linear programming problem of tea industry with interval objectives
Article history: Received December 10, 2013 Received in revised format 25 June 2014 Accepted June 26 2014 Available online July 9 2014 In this paper, we have modeled a decision making problem of a tea industry as a multi objective optimization problem in interval environment. The goal of this problem is to maximize the overall profit as well as to minimize the total production cost subject to the given resource constraints depending on budget, storage space and allotted processing times in different machines. For this purpose, the problem has been formulated as a multi objective integer linear programming problem with interval objectives. To solve the problem, we have proposed extended elitist non dominated sorting genetic algorithm (ENSGA II) for integer variables with interval fitness, crowded tournament selection, intermediate crossover, one neighborhood mutation and elitism. To develop this algorithm, we have proposed modified non dominated sorting and crowding distance based on interval mathematics and interval order relations. Finally, to test the performance of the proposed algorithm, a numerical example has been solved. (c) 2014 Growing Science Ltd. All rights reserved.