Bat algorithm is a novel bio-inspired stochastic optimisation algorithm. However, due to the limited exploration and exploitation capabilities, the performance is not well when dealing with some multi-modal numerical problems. In this paper, optimal forage strategy is designed to guide the search direction for each bat and a random disturbance strategy is also employed to extend the global search pattern. To test the performance, CEC2013 benchmark test suit and four other evolutionary algorithms are employed to compare, simulation results show our modification is effective.
['Xingjuan Cai', 'Xiao Zhi Gao', 'Yu Xue']
Improved bat algorithm with optimal forage strategy and random disturbance strategy