An ant colony system hybridized with a new local search for the sequential ordering problem

被引:232
作者
Gambardella, LM
Dorigo, M
机构
[1] IDSIA, CH-6928 Lugano, Switzerland
[2] Free Univ Brussels, IRIDIA, B-1050 Brussels, Belgium
关键词
ant colony optimization; ant algorithms; metaheuristics; sequential ordering problem; swarm intelligence;
D O I
10.1287/ijoc.12.3.237.12636
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
We present a new local optimizer called SOP-3-exchange for the sequential ordering problem that extends a local search for the traveling salesman problem to handle multiple constraints directly without increasing computational complexity. An algorithm that combines the SOP-3-exchange with an Ant Colony Optimization algorithm is described, and we present experimental evidence that the resulting algorithm is more effective than existing methods for the problem. The best-known results for many of a standard test set of 22 problems are improved using the SOP-a-exchange with our Ant Colony Optimization algorithm or in combination with the MPO/Al algorithm (Chen and Smith 1996).
引用
收藏
页码:237 / 255
页数:19
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