A robust optimization model for production planning of perishable products

S. Leung · Kin Keung Lai · W-L Ng · Yue Wu

31 citations0/0 files storedJournal of the Operational Research Society

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Supply Chain and Inventory Management Management and Optimization Techniques Optimization and Mathematical Programming

Abstract

In this study, a robust optimization model is developed to solve production planning problems for perishable products in an uncertain environment in which the setup costs, production costs, labour costs, inventory costs, and workforce changing costs are minimized. Using the concept of postponement, the production process for perishable products is differentiated into two phases to better utilize the resources. By adjusting penalty parameters, decision-makers can determine an optimal production loading plan and better utilize resources while considering different economic growth scenarios. A case from a Hong Kong plush toy company is studied and the characteristics of perishable products are discussed. Numerical results demonstrate the robustness and effectiveness of the proposed model. An analysis of the trade-off between solution robustness and model robustness is also presented.

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References

2010Stochastic Programming 1995Robust Optimization of Large-Scale Systems 1995Stochastic Programming 1970Principles of Operations Research.2001Generating Scenario Trees for Multistage Decision Problems 1998Supply Chain Postponement and Speculation Strategies: How to choose the right strategy 2001The rediscovery of postponement a literature review and directions for research 2000A robust optimization model for stochastic logistic problems

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