A Robust Optimization Framework for Analyzing Distribution Systems with Transshipment

Melvyn Sim (dscsimmnus.edu.sg)
Chou Mabel (bizchoumnus.edu.sg)
Rick So (rsouci.edu)

Abstract: This paper studies a distribution system consisting of multiple retail locations with transshipment operations among the retailers. Due to the difficulty in computing the optimal solution imposed by the transshipment operations and in estimating shortage cost from a practical perspective, we propose a robust optimization framework for analyzing the impact of transshipment operations on such a distribution system. We demonstrate that our proposed robust optimization framework is analytically tractable and is computationally efficient for analyzing even large-scale distribution systems. From a numerical study using this robust optimization framework, we address a number of managerial issues regarding the impact of transshipment on reducing the costs of the distribution system under different system configurations and retailer characteristics. In particular, we consider two system configurations, line and circle, and study how inventory holding cost, transshipment cost, and demand size and variability affect the effectiveness of transshipment operations for the cases of both homogeneous and non-homogeneous retailers. The managerial insights obtained from our robust optimization framework can help to evaluate the potential benefits when investing in transshipment operations.

Keywords: Robust Optimization, Stochastic Programming, Chance Constraint SOCP, Supply Chain Management

Category 1: Robust Optimization

Category 2: Stochastic Programming

Category 3: Applications -- OR and Management Sciences (Supply Chain Management )

Citation: Working Paper, NUS Business School

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Entry Submitted: 02/08/2006
Entry Accepted: 02/09/2006
Entry Last Modified: 02/08/2006

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