基于改进金球算法的同时取货车辆路径问题

2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) Pub Date : 2018-06-01 DOI:10.1109/ICIS.2018.8466513

Kanjana Ruttanateerawichien, W. Kurutach

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引用次数: 3

摘要

针对众所周知的车辆路径问题，改进了Golden Ball (IGB)算法，该算法同时考虑了送货订单和取货订单的客户需求。这个问题的目标是确定最优路线集，以完全满足客户群体的送货和取货需求。本文对金球(GB)算法进行了改进，采用步内改进算法修改了过程选择球员和训练程序。目的是找到使总成本最小化的解决方案。计算结果表明，IGB算法具有很强的竞争力，在各个方向上都优于金球(GB)算法。此外，在67.43%的测试实例(28个中的19个)中也获得了最知名的解决方案。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An Improved Golden Ball Algorithm for the Vehicle Routing Problem with Simultaneous Pickup and Delivery

A Golden Ball (IGB) algorithm was improved for the well-known vehicle routing problem, which simultaneously considers the customer demand from both delivery and pickup orders. The objective of this problem was to determine the optimal set of routes to totally satisfy both the delivery and pickup demand of the customer population. In this paper, the Golden Ball (GB) algorithm was improved using intra-move improvement algorithms modify process selection players and coaching procedure. The aim was to find the solution that minimizes the total cost. Computational results showed that the IGB algorithm was competitive and outperforms the Golden Ball (GB) algorithm in all directions. Moreover, the best known solutions were also obtained in 67.43% of tested instances (19 out of 28).

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2018 IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS)

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