A tabu search based hybrid evolutionary algorithm for the max-cut problem

被引:20
作者
Wu, Qinghua [1 ]
Wang, Yang [2 ]
Lu, Zhipeng [3 ]
机构
[1] Huazhong Univ Sci & Technol, Sch Management, Wuhan 430074, Peoples R China
[2] Northwestern Polytech Univ, Sch Management, Xian 710072, Peoples R China
[3] Huazhong Univ Sci & Technol, Sch Comp Sci & Technol, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Max-cut; Metaheuristics; Hybrid evolutionary algorithm; Tabu search; LOCAL SEARCH;
D O I
10.1016/j.asoc.2015.04.033
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents a tabu search based hybrid evolutionary algorithm (TSHEA) for solving the max-cut problem. The proposed algorithm integrates a distance-and-quality based solution combination operator and a tabu search procedure based on neighborhood combination of one-flip and constrained exchange moves. Comparisons with leading reference algorithms from the literature disclose that the proposed algorithm discovers new best solutions for 15 out of 91 instances, while matching the best known solutions on all but 4 instances. Analysis indicates that the neighborhood combination and the solution combination operator play key roles to the effectiveness of the proposed algorithm. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:827 / 837
页数:11
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