Sourcing under supply disruption with capacity-constrained suppliers

Purpose - The paper proposes multi-sourcing models for optimal order allocation in newsvendor setting under supply disruption with stochastic demand where suppliers are capacity constrained. Design/methodology/approach - Mathematical models are constructed to describe the stochastic single period two echelon supply chain. We first investigate the uncapacitated suppliers' problem. Then capacity constraint is included in the model to study the effect on sourcing decision. A numerical example and its solution are included to illustrate the solution procedure. We find the solution using traditional optimization approach, genetic algorithm and simulation optimization approach. Findings - The models capture the impact of disruption risk on optimal sourcing decision. When demand is highly uncertain the order should be place with the lowest cost suppliers in case of uncapacitated problem; whereas, it is to be appropriately split among a set of low-cost suppliers in case of capacitated problem. Simulation optimization found to be the best solution approach for such problem. Research implications/limitations - The model is applicable for a single period short-life cycle product. Originality/value - The models can be utilized for any number of suppliers. The numerical study illustrates the impact of probability of disruption, its consequences and cost of purchase on sourcing decisions.