Development of multi-period, multi-product model to mitigate supply risk with capacity constraint and discount

In this study, a multi-period multi-product model of mixed integer programming formulation is developed in which the firm uses a variety of techniques to mitigate its supply chain risk. The Decision is made regarding utilization of business insurance and parameters affecting on it. In addition, the amount of order quantity, inventory, recycling, re-production, product, and raw material production, and the price are determined. The topic of discount by unreliable suppliers makes the model impossible to be solved by exact methods in larger-size instances. So, this paper decomposes the multi-product model into some single-product ones with relaxing one constraint by using genetic algorithm (GA), particle swarm optimization (PSO), and PSO-GA, then presents a solution for it. The results indicated that this decomposition leads to a noticeable reduction in the running time with acceptable accuracy, especially for PSO-GA.