A single-retailer multi-supplier multi-product inventory model with destructive testing acceptance sampling and inflation

In this paper, a multi-product inventory problem is investigated in which a retailer buys items from different suppliers based on their purchasing costs and defective rates. Due to the warehouse and staff constraints involved, the inventory cycle consists of two parts. The first part corresponds to a screening period in which a destructive testing acceptance-sampling plan is used to accept or reject a lot. The other part is for selling the items. In the screening period, a lot that is rejected is returned to the suppliers where another lot is claimed for substitution at no cost. Shortage occurs during the screening period and the defective items are sold at a lower price at the end of the second part of the cycle. As we show that the problem belongs to the class of NP-hard problems, a particle swarm optimization (PSO) and a genetic algorithm (GA) is used to solve it.