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A general variable neighborhood search for solving the multi-objective open vehicle routing problem
Journal of Heuristics ( IF 1.1 ) Pub Date : 2017-12-23 , DOI: 10.1007/s10732-017-9363-8
Jesús Sánchez-Oro , Ana D. López-Sánchez , J. Manuel Colmenar

The multi-objective open vehicle routing problem (MO-OVRP) is a variant of the classic vehicle routing problem in which routes are not required to return to the depot after completing their service and where more than one objective is optimized. This work is intended to solve a more realistic and general version of the problem by considering three different objective functions. MO-OVRP seeks solutions that minimize the total number of routes, the total travel cost, and the longest route. For this purpose, we present a general variable neighborhood search algorithm to approximate the efficient set. The performance of the proposal is supported by an extensive computational experimentation which includes the comparison with the well-known multi-objective genetic algorithm NSGA-II.

中文翻译:

解决多目标开放式车辆路径问题的通用变量邻域搜索

多目标开放式车辆选路问题(MO-OVRP)是经典车辆选路问题的一种变体,其中,在完成服务后不需要路线返回仓库,并且优化了多个目标。这项工作旨在通过考虑三个不同的目标函数来解决该问题的更实际和更一般的版本。MO-OVRP寻求的解决方案可以最大程度地减少路线总数,总旅行成本和最长路线。为此,我们提出了一种通用的变量邻域搜索算法来近似有效集。这项提案的执行受到广泛的计算实验的支持,其中包括与著名的多目标遗传算法NSGA-II的比较。
更新日期:2017-12-23
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