Pareto强度值演化算法求解多目标优化问题

近年来,多目标优化问题求解已成为演化计算的一个重要研究方向,而基于Pareto最优概念的多目标演化算法则是当前演化计算的研究热点.多目标演化算法的研究目标是使算法种群快速收敛并均匀分布于问题的非劣最优域.本文定义和使用稀松密度来保持群体中个体的均匀分布,并将个体的Pareto强度值和稀松密度合并到个体的适应值定义中.通过对测试函数的实验,验证了算法的可行性和有效性.

Pareto Strength Evolutionary Algorithm for Multi-Objective Optimization Problem

Multi-Objective Optimization(MOO) has become an important research area of evolutionary computations in recent years, and the current research work focuses on the Pareto optimal-based MOO evolutionary approaches. The paper define and use loosing density to maintain a good spread of solution in the population,and define the fitness of the individual through Pareto strength and crowding density. Test results show that the new approach is feasible and effective.