A Particle Swarm Optimization Approach for Route Planning with Cross-Docking

Mu Chen Chen, Yu Hsiang Hsiao, Himadeep Reddy, Manoj Kumar Tiwari

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

In cross-docking operations, planners need to coordinate the inbound, docking and outbound logistics operations to ensure a smooth flow of goods across the supply chain. The operation management of cross docking is a crucial task with high complexity for the logistics systems. This paper attempts to address the Vehicle Routing Problems (VRPs) of distribution centers with multiple cross-docks for processing multiple products. In this paper, the mathematical model intends to minimize the total cost of operations subjected to a set of time and capacity constraints. Due to high complexity of model, a variant of Particle Swarm Optimization (PSO) with a Self-Learning approach is tailored to solve the VRP. Two test problems are generated and results are obtained.

Original languageEnglish
Title of host publicationProceedings - 2015 7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015
PublisherIEEE Computer Society
Pages1-6
Number of pages6
ISBN (Electronic)9781467383059
DOIs
StatePublished - 3 Mar 2016
Event7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015 - Kobe, Japan
Duration: 18 Nov 201520 Nov 2015

Publication series

NameInternational Conference on Emerging Trends in Engineering and Technology, ICETET
Volume2016-March
ISSN (Print)2157-0477
ISSN (Electronic)2157-0485

Conference

Conference7th International Conference on Emerging Trends in Engineering and Technology, ICETET 2015
CountryJapan
CityKobe
Period18/11/1520/11/15

Keywords

  • Cross-Docks
  • E-Logistics
  • Particle Swarm Optimization
  • Supply Chain Management
  • Vehicle Routing Problem

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