Improved artificial bee colony algorithm and its application in engineering design

Abstract

In order to solve the multi-objective optimization problem (MOP: Multi-Objective Problem), the artificial bee colony algorithm (ABC) has the problems of difficulty in collecting and maintaining the diversity of candidate solutions. The solution strategies of each part are improved. Based on the ABC algorithm framework, a multi-objective ABC algorithm based on adaptive solution strategy is designed. The proposed improved multi-objective ABC is compared with other typical swarm intelligence algorithms in the practical application engineering design problem of electromechanical actuator design. Experimental verification shows that the proposed MOABC/DD (Multi-Objective Artificial Bee Colony Based on Dominance and Decomposition) algorithm has better problem solving accuracy than typical algorithms when solving the benchmark test case of electromechanical actuator design problem. In addition, the experimental results of MOABC/DD are relatively stable, which proves that MOABC/DD has high solution stability and robustness. Keywords: multi-objective optimization problem.