JUCS - Journal of Universal Computer Science 23(7): 652-672, doi: 10.3217/jucs-023-07-0652
An Adaptive Membrane Evolutionary Algorithm for Solving Constrained Engineering Optimization Problems
expand article infoJianhua Xiao, Ying Liu, Shuai Zhang§, Ping Chen
‡ Nankai University, Tianjin, China§ University of Manitoba, Winnipeg, Canada
Open Access
In this paper, an adaptive membrane evolutionary algorithm (AMEA) is proposed, which combines a dynamic membrane structure and a differential evolution with the adaptive mutation factor. In the AMEA, the feasibility proportion method is used to dynamically adjust the size of the elementary membrane in the optimization process. The results of the experimental indicate that the proposed algorithm outperforms other evolutionary algorithms on five well-known constrained engineering optimization problems.
membrane computing, membrane algorithm, differential evolution, engineering optimization problem