首页> 外文会议>IEEE International Conference on Industrial Engineering and Engineering Management >Developing an improved particle swarm optimization algorithm for solving the inventory routing problem with direct shipment
【24h】

Developing an improved particle swarm optimization algorithm for solving the inventory routing problem with direct shipment

机译:开发一种改进的粒子群优化算法,用于用直接发货解决库存路由问题

获取原文

摘要

This paper considers a multi-period multi-product inventory routing problem whereas the objective is to minimize total system cost that includes production setup, inventory and distribution costs. The problem integrates decisions on the production planning, inventory management and distribution planning. Here, we assume that products are produced and delivered from one manufacturer to a set of retailers through a fleet of homogenous capacitated vehicles under direct shipping strategy. Since the problem is known as an NP-hard problem, this paper proposes an improved particle swarm optimization algorithm for solving the problem. The efficiency and the reliability of the proposed algorithm are evaluated by using various test problems with different sizes that is randomly generated. The performance of the developed algorithm is compared with two different algorithms: Particle Swarm Optimization, and Genetic Algorithm. The numerical results show that the developed algorithm outperforms benchmark algorithms, especially for the large-sized problems.
机译:本文考虑了多个多时期的多产品库存路由问题,而目标是最大限度地减少包括生产设置,库存和分配成本的总系统成本。问题集成了生产规划,库存管理和分配规划的决策。在这里,我们假设产品由一个制造商生产并通过一组零售商通过直接运输策略的同源电容车队。由于该问题被称为NP难题,提出了一种改进的粒子群优化算法来解决问题。通过使用随机生成的不同大小的各种测试问题来评估所提出的算法的效率和可靠性。将开发算法的性能与两种不同的算法进行比较:粒子群优化和遗传算法。数值结果表明,发达的算法优于基准算法,特别是对于大型问题。

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