抽象的

WK-means and branch-boundmethod based for cloud logistics scheduling

Xun-Yi Ren, Da-Rong Yuan


The efficient and accurate logistics scheduling problem has become the bottleneck that impedes the e-commerce development of China. Cloudbased logistics can achieve resource sharing and centralized logistics scheduling, which is expected to fundamentally solve the problems encountered in logistics scheduling. However, the current research about cloud logistics scheduling is only the beginning. Most methods based on exact algorithms and heuristic scheduling algorithms are timeconsuming and inefficientwhile efficient scheduling algorithmis relatively scarce. This article takes cloud logistics scheduling problemas a NP-hard problem with multi-constraint and multi-objective decision making and establishes a multi-objective optimization cloud logistics scheduling model. K-means algorithmis used to cluster large and complex distribution network, but due to the load balancing problem in practical application, we useWK-means cluster which take the weight as an external constraints to balance the workload between each cluster. Large-scale VRP problem will eventually be divided into point-to-point TSP problemwhich we can use the branch-bound to solve and optimize. Simulation results show that the proposed scheme is more accurate and efficient than the existing typical heuristic scheduling method.


免责声明: 此摘要通过人工智能工具翻译,尚未经过审核或验证

索引于

  • 中国社会科学院
  • 谷歌学术
  • 打开 J 门
  • 中国知网(CNKI)
  • 引用因子
  • 宇宙IF
  • 电子期刊图书馆
  • 研究期刊索引目录 (DRJI)
  • 秘密搜索引擎实验室
  • ICMJE

查看更多

期刊国际标准号

期刊 h 指数

Flyer