Solving A Kind of High Complexity Multi-Objective Problems by A Fast Algorithm

被引：0
|
作者：
Zeng San-you
Department of Computer Science
State Key Laboratory of Software Engineering
机构：
来源：
Wuhan University Journal of Natural Sciences | 2003年 / S1期
基金：
中国国家自然科学基金;
关键词：
evolutionary algorithms; orthogonal design; multi-objective optimization; Pareto-optimal set;
D O I：
暂无
中图分类号：
O224 [最优化的数学理论];
学科分类号：
070105 ; 1201 ;
摘要：
A fast algorithm is proposed to solve a kind of high complexity multi-objective problems in this paper. It takes advantages of both the orthogonal design method to search evenly, and the statistical optimal method to speed up the computation. It is very suitable for solving high complexity problems, and quickly yields solutions which converge to the Pareto-optimal set with high precision and uniform distribution. Some complicated multi-objective problems are solved by the algorithm and the results show that the algorithm is not only fast but also superior to other MOGAS and MOEAs, such as the currently efficient algorithm SPEA, in terms of the precision, quantity and distribution of solutions.
引用
收藏
页码：183 / 188
页数：6
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