A Membrane-Inspired Evolutionary Algorithm Based on Population P Systems and Differential Evolution for Multi-Objective Optimization

作者：Cheng Jixiang; Zhang Gexiang^*; Wang Tao

来源：Journal of Computational and Theoretical Nanoscience, 2015, 12(7): 1150-1160.

DOI：10.1166/jctn.2015.3866

• Membrane-Inspired Evolutionary Algorithm
• Population P Systems
• Differential Evolution
• Multi-Objective Optimization

This paper proposes a membrane-inspired evolutionary algorithm based on population P systems and differential evolution for multi-objective optimization. In the algorithm, the cells of population P systems are divided into two groups. The first group, consisting of most of cells, focuses on evolving objects using differential evolution rules while the second group, consisting of only one cell, aims at selecting and re-distributing objects across the first group of cells for next generation using a special selection rule. Moreover, the communications among cells are performed at both local and global levels in order to obtain well converged and distributed solution set. Twelve benchmark problems with diverse features are utilized to test algorithm performance. Experimental results show that the proposed approach outperforms five well-known algorithms in terms of three performance metrics.

• 出版日期2015-7
• 单位西南交通大学