Sourcing decisions with order allocation under supply disruption risk considering quantitative and qualitative criteria

This paper addresses sourcing decisions with order allocation in the presence of supplier disruption risks in a two-echelon supply chain considering both quantitative and qualitative aspects. A mixed-integer linear program is proposed for the optimal supplier selection and order allocation considering finite and expandable production capacity, failure probability, all-unit price discount, and spot-market cost. Due to the time complexity of the problem to get an optimal solution, we develop a heuristic which is found highly efficient in time complexity and highly competitive in solution quality. A multi-objective model is formulated to capture the qualitative aspect of suppliers by maximizing the total purchase value along with minimizing the expected total cost. We have applied NSGA-II and MOPSO, two widely used evolutionary algorithms, to solve the multi-objective model. A numerical illustration is presented along with sensitivity analysis considering a supplier base of twenty suppliers and a sourcing strategy up to six suppliers. It has been found that dual-sourcing and triple-sourcing are mainly part of the non-dominated Pareto front. Also, increasing demand would lead to a higher level of sourcing strategy, which also depends on the maximum capacity of suppliers and the minimum order to be allocated to the selected suppliers.