Intelligent Algorithms for solving multiobjective optimization problems

被引：0
|
作者：
Yi Hong-Xia [1 ]
Xiao Liu [1 ]
Liu Pu-Kun [1 ]
机构：
[1] Chinese Acad Sci, Inst Elect, Beijing 100190, Peoples R China
来源：
2008 4TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS, NETWORKING AND MOBILE COMPUTING, VOLS 1-31 | 2008年
关键词：
Multiobjective optimization; Genetic Algorithm; Particle Swarm optimization; Simulated Annealing; Ant Colony Algorithms;
D O I：
暂无
中图分类号：
TN [电子技术、通信技术];
学科分类号：
0809 ;
摘要：
This paper presents a comprehensive survey of many evolutionary algorithms for solving multiobjective optimization problems. Four main kinds of multiobjective algorithms (GA, PSO, SA, and AC) have been presented, and their merits and demerits are compared and discussed respectively. Finally, a mix algorithm is suggested as an effective method.
引用
收藏
页码：13101 / 13105
页数：5
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