A tabu search based memetic algorithm for the maximum diversity problem

被引:33
|
作者
Wang, Yang [1 ,2 ]
Hao, Jin-Kao [2 ]
Glover, Fred [3 ]
Lu, Zhipeng [4 ]
机构
[1] Northwestern Polytech Univ, Sch Management, Xian 710072, Peoples R China
[2] Univ Angers, LERIA, F-49045 Angers, France
[3] OptTek Syst Inc, Boulder, CO 80302 USA
[4] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
关键词
Combinatorial optimization; Maximum diversity problem; Metaheuristics; Tabu search; Memetic algorithm; OPTIMIZATION; GREEDY; GRASP;
D O I
10.1016/j.engappai.2013.09.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents a highly effective memetic algorithm for the maximum diversity problem based on tabu search. The tabu search component uses a successive filter candidate list strategy and the solution combination component employs a combination operator based on identifying strongly determined and consistent variables. Computational experiments on three sets of 40 popular benchmark instances indicate that our tabu search/memetic algorithm (TS/MA) can easily obtain the best known results for all the tested instances (where no previous algorithm has achieved) as well as improved results for six instances. Analysis of comparisons with state-of-the-art algorithms demonstrates statistically that our TS/MA competes very favorably with the best performing algorithms. Key elements and properties of TS/MA are also analyzed to disclose the benefits of integrating tabu search (using a successive filter candidate list strategy) and solution combination (based on critical variables). (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:103 / 114
页数:12
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