Comparison of local search implementation schemes in hybrid evolutionary multiobjective optimization algorithms

被引：0

作者：

Ishibuchi, H ^{[1
]}

Narukawa, K ^{[1
]}

机构：

[1] Osaka Prefecture Univ, Dept Ind Engn, Osaka, Japan

来源：

HIS'04: FOURTH INTERNATIONAL CONFERENCE ON HYBRID INTELLIGENT SYSTEMS, PROCEEDINGS | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We compare two implementation schemes of local search in hybrid evolutionary multiobjective optimization algorithms. One is based on the weighted sum of multiple objectives, and the other is based on Pareto dominance. These two implementation schemes are compared with each other through computational experiments on a knapsack problem and a flowshop scheduling problem. We also examine a simple modification of the weighted sum-based scheme.

引用

页码：404 / 409

页数：6

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