期刊
COMPUTERS & OPERATIONS RESEARCH
卷 37, 期 11, 页码 1939-1951出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2009.12.005
关键词
Metaheuristics; Probabilistic traveling salesman problem; Empirical estimation
类别
资金
- European Commission [MEST-CT-2004-505079]
- French Community of Belgium
- F.R.S.-FNRS of the French Community of Belgium
The probabilistic traveling salesman problem (PTSP) is a central problem in stochastic routing. Recently, we have shown that empirical estimation is a promising approach to devise highly effective local search algorithms for the PTSP. In this paper, we customize two metaheuristics, an iterated local search algorithm and a memetic algorithm, to solve the PTSP. This customization consists in adopting the estimation approach to evaluate the solution cost, exploiting a recently developed estimation-based local search algorithm, and tuning the metaheuristics parameters. We present an experimental study of the estimation-based metaheuristic algorithms on a number of instance classes. The results show that the proposed algorithms are highly effective and that they define a new state-of-the-art for the PTSP. (C) 2009 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据