Iterated fast local search algorithm for solving quadratic assignment problems

被引：22
|
作者：
Ramkumar, A. S.
Ponnambalam, S. G. [1 ]
Jawahar, N. [2 ]
Suresh, R. K.
机构：
[1] Monash Univ, Sch Sci & Engn, Clayton, Vic 3168, Australia
[2] Thiagarajar Coll Engn, Madurai, Tamil Nadu, India
来源：
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING | 2008年 / 24卷 / 03期
关键词：
facility layout; QAP; optimization; evolutionary algorithm;
D O I：
10.1016/j.rcim.2007.01.004
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper concentrates on multi-row machine layout problems that can be accurately formulated as quadratic assignment problems (QAPs). A genetic algorithm-based local search approach is proposed for solving QAPs. In the proposed algorithm, three different mutation operators namely adjacent, pair-wise and insertion or sliding operators are separately combined with a local search method to form a mutation cycle. Effectiveness of introducing the mutation cycle in place of mutation is studied. Performance of the proposed iterated approach is analyzed and the solution qualities obtained are reported. (C) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码：392 / 401
页数：10
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