An Improved Population Migration Algorithm for Solving Multi-Objective Optimization Problems

被引：2
|
作者：
Zhao, Qian [1 ]
Liu, Xueying [1 ]
Wei, Shujun [2 ]
机构：
[1] Inner Mongolia Univ Technol, Coll Sci, Hohhot 010051, Peoples R China
[2] Inner Mongolia Univ Finance & Econ, Coll Comp Informat Management, Hohhot 010070, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS | 2012年 / 5卷 / 05期
关键词：
population migration algorithm; multi-objective optimization; vector-evaluated method; dynamic weighted aggregation; population flow mode;
D O I：
10.1080/18756891.2012.733232
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The population migration algorithm is a very effective evolutionary algorithm for solving single-objective optimization problems, but very few applications are available for solving multi-objective optimization problems (MOPs). The current study proposes an improved population migration algorithm for solving MOPs based on the vector evaluated method and the dynamic weighted aggregation. The local search ability of the improved algorithm is greatly increased by using the population flow mode. The convergence of the improved algorithm is also proven. Performance metrics and experimental test results show that the improved algorithm is very feasible and effective for solving MOPs.
引用
收藏
页码：933 / 941
页数：9
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