一种基于膜系统理论的多目标演化算法

提出一种用于求解多目标优化问题的基于膜系统理论的演化算法. 受膜系统理论的功能和处理化合物方式的启发，设计了求解多目标优化问题的演化操作. 此外，在表层膜中，引入了非支配排序和拥挤距离两种机制改善算法的搜索效率. 采用ZDT（Zitzler-Deb-Thiele）和DTLZ（Deb-Thiele-Laumanns-Zitzler）多目标问题对所提算法进行测试，所提算法求得的候选解既能较好地逼近真实Pareto前沿，又能满足非支配解集多样性的要求. 仿真结果表明，所提方法求解多目标优化问题是可行和有效的.

A Multi-objective Evolutionary Algorithm Based on Membrane System Theory

In this paper, an evolutionary algorithm based on the membrane system theory has been proposed for multi-objective optimization problems. Inspired by the function and the compound reaction of the membrane system theory, the evolutionary operators are designed to solve the multi-objective optimization problems. In addition, the non-dominated sorting and the crowding distance are introduced into the skin membrane to improve the search efficiency of the algorithm. The multi-objective optimization problems including ZDT (Zitzler-Deb-Thiele) and DTLZ (Deb-Thiele-Laumanns-Zitzler) are employed to evaluate the performance of the algorithm. The proposed algorithm can not only obtain quickly the approximate Pareto front but also satisfy the requirement of diversity of Pareto front. Simulation results indicate that the proposed algorithm is feasible and effective.