期刊
COMPUTERS & OPERATIONS RESEARCH
卷 40, 期 7, 页码 1661-1670出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.cor.2012.12.015
关键词
Stochastic vehicle routing; Monte Carlo sampling; Local search; Random restart local search
类别
资金
- Swiss National Science Foundation [200021-120039/1, 200020-134675/1]
- Swiss National Science Foundation (SNF) [200021-120039, 200020_134675] Funding Source: Swiss National Science Foundation (SNF)
The Probabilistic Traveling Salesman Problem with Deadlines (PTSPD) is a Stochastic Vehicle Routing Problem with a computationally demanding objective function. In this work we propose an approximation for that objective function based on Monte Carlo Sampling and using the novel approach of quasi-parallel evaluation of samples. We perform comprehensive computational studies that reveal the efficiency of this approximation. Additionally, we examine different Local Search Algorithms and present a Random Restart Local Search Algorithm for solving the PTSPD together with an extensive computational study on a large set of benchmark instances. (C) 2013 Elsevier Ltd. All rights reserved.
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