Optimization of cost and service level in the presence of supply chain disruption risks: Single vs. multiple sourcing

• Published in: Computers & operations research Vol. 51; pp. 11 - 20
• Main Author: Sawik, Tadeusz
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.11.2014; Elsevier; Pergamon Press Inc
• Subjects: Applied sciences; Decision analysis; Decision theory. Utility theory; Disruption risks; Exact sciences and technology; Firm modelling; Integer programming; Inventory control, production control. Distribution; Logistics; Mixed integer programming; Operational research and scientific management; Operational research. Management science; Risk management; Single vs. multiple sourcing; Sourcing; Stochastic scheduling; Studies; Supplier selection; Suppliers; Supply chain management; Supply chains; Supplier selection; Stochastic scheduling; Mixed integer programming; Single vs. multiple sourcing; Disruption risks; Costs; Ordered set; Worst case method; Financial management; Subcontracting; Supply disruption; Combinatorial optimization; Purchasing; Shortage; User service; Supplier; Purchases; Firm strategy; Probabilistic approach; Coordination; Decision making; Scheduling; Order picking; Due date; Stochastic programming; Risk aversion; Integer programming; Production management; Supplier customer relationship; Objective function; Planning; Risk management; Service quality; Logistics
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2014.04.006

The coordinated supplier selection and customer order scheduling in the presence of supply chain disruption risks is studied for single and multiple sourcing strategies. Given a set of customer orders for products, the decision maker needs to select a single supplier or a subset of suppliers for purchasing parts required to complete the customer orders, and schedule the orders over the planning horizon, to mitigate the impact of disruption risks. The suppliers are located in different geographic regions and the supplies are subject to different types of disruptions: to random local disruptions of each supplier individually, to random regional disruptions of all suppliers in the same region simultaneously and to random global disruptions of all suppliers simultaneously. For any combination of suppliers hit by different types of disruptions, a formula for calculating the corresponding disruption probability is developed. The obtained combinatorial stochastic optimization problem is formulated as a mixed integer program with conditional value-at-risk as a risk measure. The problem objective is either to minimize expected worst-case cost or to maximize expected worst-case customer service level, i.e., the expected worst-case fraction of customer orders filled on or before their due dates. The risk-averse solutions that optimize worst-case performance of a supply chain under disruptions risks are compared for the two sourcing strategies and the two objective functions. Numerical examples and computational results are presented and some managerial insights on the choice between the two sourcing strategies are reported.