Multi-directional local search

被引:60
|
作者
Tricoire, Fabien [1 ,2 ]
机构
[1] Univ Vienna, Dept Business Adm, A-1210 Vienna, Austria
[2] UNSW, NICTA, Sydney, NSW, Australia
基金
奥地利科学基金会;
关键词
Multi-objective optimization; Metaheuristics; MULTIOBJECTIVE EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHM; KNAPSACK-PROBLEM; OPTIMIZATION; PERFORMANCE; MAKESPAN; FLOWTIME;
D O I
10.1016/j.cor.2012.03.010
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper introduces multi-directional local search, a metaheuristic for multi-objective optimization. We first motivate the method and present an algorithmic framework for it. We then apply it to several known multi-objective problems such as the multi-objective multi-dimensional knapsack problem, the bi-objective set packing problem and the bi-objective orienteering problem. Experimental results show that our method systematically provides solution sets of comparable quality with state-of-the-art methods applied to benchmark instances of these problems, within reasonable CPU effort. We conclude that the proposed algorithmic framework is a viable option,when solving multi-objective optimization problems. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:3089 / 3101
页数:13
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