Title

A novel multi-objective meta-heuristic model for solving cross-docking scheduling problems

Document Type

Article

Publication Date

2-27-2015

DOI

https://doi.org/10.1016/j.asoc.2015.02.030

Abstract

Cross-docking is a material handling and distribution technique in which products are transferred directly from the receiving dock to the shipping dock, reducing the need for a warehouse or distribution center. This process minimizes the storage and order-picking functions in a warehouse. In this paper, we consider cross-docking in a supply chain and propose a multi-objective mathematical model for minimizing the make-span, transportation cost and the number of truck trips in the supply chain. The proposed model allows a truck to travel from a supplier to the cross-dock facility and from the supplier directly to the customers. We propose two meta-heuristic algorithms, the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective particle swarm optimization (MOPSO), to solve the multi-objective mathematical model. We demonstrate the applicability of the proposed method and exhibit the efficacy of the procedure with a numerical example. The numerical results show the relative superiority of the NSGA-II method over the MOPSO method.

Language

English

Comments

Mohtashami, A., Tavana, M., Santos-Arteaga, F.J. and Fallahian-Najafabadi, A. (2015) ‘A Novel Multi-Objective Meta-Heuristic Model for Solving Cross-Docking Scheduling Problems,’ Applied Soft Computing, Vol. 31, pp. 30-47.

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