Developing a cross-docking network design model under uncertain environment

S M Seyedhoseini,E Teimoury,Reza Rashid

doi:10.1007/s40092-014-0088-0

S M Seyedhoseini, E Teimoury + Show 1 more

Open Access

https://doi.org/10.1007/s40092-014-0088-0

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Abstract

Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time. Paying attention to these concerns, and importance of the congestion in cross docks, we present a mixed-integer model to optimize the location and design of cross docks at the same time to minimize the total transportation and operating costs. The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock. To prepare a perfect illustration for performance of the model, a real case also has been examined that indicated effectiveness of the proposed model.

Highlights

In the competitive environment, companies must satisfy more complicated demands with less response time
Cross-docking is a logistic concept, which plays an important role in supply chain management by decreasing inventory holding, order packing, transportation costs and delivery time
The model combines queuing theory for design aspects, for that matter, we consider a network of cross docks and customers where two M/M/c queues have been represented to describe operations of indoor trucks and outdoor trucks in each cross dock

Summary

Introduction

Companies must satisfy more complicated demands with less response time. Mousavi and Tavakoli-Moghaddam (2013) considered location and routing scheduling problems with cross-docking, and present a two-stage mixed-integer programming model. Tavakkoli-moghaddam et al (2013) considered a network design problem for a three level supply chain, and proposed a new mathematical model, where their aims were to determine the number of located distribution centers, their locations, capacity level, and allocating customers to distribution centers. Some researchers believe that it makes the problem hard to solve, and some suggest cutting planes for obtaining optimal solutions in small and medium-sized problem instances (Karimi-Nasab and Seyedhoseini 2013) In this area, Ha (1997) considered Poisson demand and exponential production times for a single item make-tostock production system.

Objective

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Conclusion