Optimal inspection and advance payment policy for deteriorating items using differential evolution metaheuristic

Abstract

The deterioration of items such as fruits, eatables, etc. may influence the adjacent units and intercept the supply. In many circumstances, the existence of a spoiled unit accelerates the deterioration process. The degradation effect can be mitigated by removing the affected unit. This research investigation explores an impact of frequent inspection on the spoiling items in an inventory system and can be used as a step forward to reduce food wastage due to mutual spoilage. In many business transactions, the retailer has the ability to make judgments regarding advance payment. The present work attempts to develop a lot-sizing model for price-sensitive demand under the premise of partial advance payment and deterioration rate as a function of inspection frequency. We suggest an optimal prepayment strategy from the retailer’s point of view. A mixed-integer programming problem is formulated and solved by using a genetic algorithm (GA) and differential evolution (DE) algorithm based on different mutation strategies. It is established that DE performs better in comparison to GA. Based on some statistical measures, we have selected the mutation scheme which is most suitable for the proposed problem. The inventory-related measures are established for the proposed problem and used to present a numerical simulation and optimal inventory policy. The numerical findings show that the ideal inspection and prepayment strategy boost profitability by reducing spoilage. The managerial insights are discussed that may be beneficial in decision-making for inspection and advance payment.