Integrated selection of suppliers and scheduling of customer orders in the presence of supply chain disruption risks

This paper presents a new stochastic mixed integer programming approach to integrated supplier selection, order quantity allocation and customer order scheduling in the presence of supply chain disruption risks. Given a set of customer orders for products, the decision maker needs to decide from which supplier to purchase parts required to complete the orders, how to allocate the demand for parts among the selected suppliers, and how to schedule the customer orders over the planning horizon to minimize total cost of ordering and purchasing of parts plus penalty cost of delayed and unfulfilled customer orders and to mitigate the impact of disruption risks. The risk-neutral and risk-averse solutions that optimize, respectively average and worst-case performance of a supply chain are compared for both single and multiple sourcing strategy. Numerical examples are presented and computational results are reported.

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