一种约束多目标优化问题的改进蚁群遗传算法

该文针对多目标蚁群遗传算法(MOAGA)解集边界分布不均的问题,提出改进算法,解决了连续空间中带约束条件多目标优化问题。改进算法在基本MOAGA算法的基础上,在选择中引入一定比例的边界决策、单目标最优决策,并提高边界决策的交叉率。实验证明,改进算法解决了基本算法解集分布边界疏中间密的问题,并且能更快的获得散布性较好的Pareto最优解集。

An Improved Multi-Objective Ant-Genetic Algorithm In Constrained Problem

An improved Multi-Objective Ant-Genetic Algorithm is presented in this paper,it can be used to solve Constrained Multi-Objective Optimization Problem on continuous space.Go farther than the basic MOAGA,we introduce some scale of boundary-decision and single-objective excellent-decision in choosing,and enhance ratio of intercrossing of boundary-decision.In the end,an example was listed to prove that the improved algorithm can solve the problem of the solution-set distributing uneven on the boundary in basic one,and can obtain the Pareto optimality set faster and better.