Probabilistic diversification and intensification in local search for vehicle routing
Probabilistic diversification and intensification in local search for vehicle routing
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DOI：
10.1007/bf02430370
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发表时间：
1995-09
影响因子：
2.7
通讯作者：
Yves Rochat;É. Taillard
中科院分区：
文献类型：
--
作者：
Yves Rochat;É. Taillard
本文提出了一种用于求解车辆路径问题的分散、强化和并行化局部搜索的概率技术。这种技术可以应用于各种各样的车辆路线问题和局部搜索。结果表明，该方法可显著提高车辆路径问题的一级禁忌搜索效率。此外，这种技术产生的解决方案还可以通过本文中介绍的后优化技术进行改进。对文献中近40个问题实例的解法进行了改进。
This article presents a probabilistic technique to diversify, intensify, and parallelize a local search adapted for solving vehicle routing problems. This technique may be applied to a very wide variety of vehicle routing problems and local searches. It is shown that efficient first-level tabu searches for vehicle routing problems may be significantly improved with this technique. Moreover, the solutions produced by this technique may often be improved by a postoptimization technique presented in this article, too. The solutions of nearly forty problem instances of the literature have been improved.