求解多目标优化问题的新遗传算法

计算机科学 ›› 2013, Vol. 40 ›› Issue (Z6): 64-66.

求解多目标优化问题的新遗传算法

韩丽霞

中国矿业大学计算机学院徐州221116

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金项目(60873099)资助

Novel Genetic Algorithm for Multi-objective Optimization Problem

HAN Li-xia

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 给出了求解多目标优化问题的一种新解法。定义了多目标优化问题的非劣方向,设计了方向杂交算子和简单的变异算子。标准算例的计算机仿真结果表明,新算法可以快速地找到一组范围广、分布均匀且数量充足的Pareto最优解。

关键词: 多目标优化,遗传算法,Pareto最优解,全局收敛

Abstract: For multi-objective optimization problems(MOP),a new algorithm was proposed．The nondominated direction was firstly defined．Then,a new crossover operator and a mutation operator were presented based on the definition．Finally,the computer simulations on benchmark problems demonstrate that the proposed algorithm is effective and can find high quality solution set in terms of convergence,diversity,and the distribution of the obtained Pareto optimal solutions.

Key words: Multi-objective optimization,Genetic algorithm(GA),Pareto optimal solution,Global convergence

韩丽霞. 求解多目标优化问题的新遗传算法[J]. 计算机科学, 2013, 40(Z6): 64-66. https://doi.org/

HAN Li-xia. Novel Genetic Algorithm for Multi-objective Optimization Problem[J]. Computer Science, 2013, 40(Z6): 64-66. https://doi.org/

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