Title: The Self-Learning Particle Swarm Optimization approach for routing pickup and delivery of multiple products with material handling in multiple cross-docks
Authors: Chen, Mu-Chen
Hsiao, Yu-Hsiang
Reddy, Reddivari Himadeep
Tiwari, Manoj Kumar
運輸與物流管理系
註:原交通所+運管所

Department of Transportation and Logistics Management
Keywords: Multiple cross-docks;Vehicle routing problem;Particle Swarm Optimization;Self-learning strategy;Genetic Algorithms
Issue Date: Jul-2016
Abstract: Vehicle Routing Problems (VRPs) in distribution centers with cross-docking operations are more complex than the traditional ones. This paper attempts to address the VRP 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 constraints. Due to high complexity of model, it is solved by using a variant of Particle Swarm Optimization (PSO) with a Self-Learning strategy, namely SLPSO. To validate the effectiveness of SLPSO approach, benchmark problems in the literature and test problems are solved by SLPSO. (C) 2016 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.tre.2016.04.003
http://hdl.handle.net/11536/133908
ISSN: 1366-5545
DOI: 10.1016/j.tre.2016.04.003
Journal: TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume: 91
Begin Page: 208
End Page: 226
Appears in Collections:Articles