Abstract
This paper presents a bi-objective stochastic mixed integer programming approach for a joint selection of suppliers and scheduling of production and distribution in a multi-tier supply chain subject to local and regional disruption risks. Two conflicting problem objectives are minimization of cost and maximization of service level. The three shipping methods are considered for distribution of products: batch shipping with a single shipment of different customer orders, batch shipping with multiple shipments of different customer orders, and individual shipping of each customer order immediately after its completion. The stochastic combinatorial optimization problem is formulated as a time-indexed mixed integer program with the weighted-sum aggregation of the two objective functions. The supply portfolio is determined by binary selection and fractional allocation variables, while time-indexed assignment variables determine the production and distribution schedules. The problem formulation incorporates supply-production, production-distribution, and supply-distribution coordinating constraints to efficiently coordinate supply, production, and distribution schedules. Numerical examples modeled after an electronics supply chain and computational results are presented and some managerial insights are reported. The findings indicate that for all shipping methods, the service-oriented supply portfolio is more diversified than the cost-oriented portfolio and the more cost-oriented decision-making, the more delayed the expected supply, production, and distribution schedules.
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Sawik, T. (2020). Integrated Selection of Supply Portfolio and Scheduling of Production and Distribution. In: Supply Chain Disruption Management. International Series in Operations Research & Management Science, vol 291. Springer, Cham. https://doi.org/10.1007/978-3-030-44814-1_6
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