...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International Journal of Services Technology and Management >Multi-depot vehicle routing problem based on customer satisfaction
【24h】

Multi-depot vehicle routing problem based on customer satisfaction

机译：基于客户满意度的多功能车辆路由问题

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Nowadays, meeting the customer's demands in the shortest time and least cost is the most challenging task of maintaining any supply chain. Vehicle routing problem (VRP) plays an important role in the logistics. In typical VRP, customers' are used to serving as a single depot, but in real-life single depot will not be sufficient to meet the customer's demand or customers' satisfaction. In this context, this article presents the multi-depot vehicle routing problem based on customer's satisfaction (MDVRPCS). Since MDVRPCS is an NP-hard problem so, ant colony optimisation (ACO) has been proposed to solve the MDVRPCS. The proposed algorithms have two phases. The first phase involves clustering the nodes into a desired number of groups. This has been done by using K-means clustering algorithm. The second phase involves optimisation of routes for each cluster. This is achieved by using ACO. The proposed algorithm has been tested for well-know problem instances from the literature. The results show that the algorithm is capable of obtaining good optimal solutions.
机译：如今，在最短的时间和最低成本中满足客户的需求是维护任何供应链的最具挑战性的任务。车辆路由问题（VRP）在物流中起着重要作用。在典型的VRP中，客户用作单个仓库，但在现实生活中，单身仓库将不足以满足客户的需求或客户的满意度。在此背景下，本文基于客户的满意度（MDVRPC）介绍了多仓库车辆路由问题。由于MDVRPC是NP难题所以，已经提出了蚁群优化（ACO）来解决MDVRPC。所提出的算法有两个阶段。第一阶段涉及将节点聚类为所需的组数。这是通过使用K-Means聚类算法来完成的。第二阶段涉及优化每个群集的路由。这是通过使用ACO实现的。已经测试了所提出的算法，以了解文献的众所周知的问题实例。结果表明，该算法能够获得良好的最佳解决方案。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号