Strategic Sourcing Under Supply Disruption Risk
Disruption in the upstream of any supply chain affects the productivity and reputation of suppliers in that chain. Supply disruption risk is prevalent and affects more suppliers especially since these suppliers tend to be grouped geographically or as clusters for greater economies of scale. With attention paid to disaster management and business contingency planning, many firms are reassessing their supply chain strategies to effectively handle such risks, contain cost, and maintain service levels. This chapter presents a Mixed Integer Linear Programming (MILP) model for supplier selection and order quantity allocation (SSOA) for suppliers who bear different disruption likelihood, capacity, upside flexibility and operate under different price discount regimes. The objective is to minimize the expected total cost comprising supplier management cost, purchasing cost, and an expected loss if a supplier’s reliability to serve is compromised by disruptions. As the SSOA problem under supply disruption risk is NP-hard, particle swarm optimization with time varying inertia weight and acceleration coefficients is applied. Numerical tests are conducted to illustrate the proposed approach and the results obtained are compared with Genetic Algorithm (GA). Sensitivity analysis is conducted on the disruption likelihood, supplier upside flexibility, and the price discount regimes.
The first author acknowledges the National Institute of Technology, Trichy, India for providing a travel grant to visit the second author under the Technical Education Quality Improvement Programme (TEQIP-II), in which this work was done. The authors thank the editor for the constructive comments.
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