The Self-Learning Particle Swarm Optimization approach for routing pickup and delivery of multiple products with material handling in multiple cross-docks

Mu-Chen Chen, Yu-Hsiang Hsiao, Reddivari Himadeep Reddy and Manoj Kumar Tiwari

Transportation Research Part E: Logistics and Transportation Review, 2016, vol. 91, issue C, 208-226

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.

Keywords: Multiple cross-docks; Vehicle routing problem; Particle Swarm Optimization; Self-learning strategy; Genetic Algorithms (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (6)

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DOI: 10.1016/j.tre.2016.04.003

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