Optimal Replenishment for Perishable Products with Inventory-Dependent Demand and Backlogging under Continuous and Discrete Progressive Payments

Managing material and cash flows attracts concerns of physical and financial departments in most companies. We, therefore, focus on optimizing the replenishment policy for a channel with stock-dependent demand considering item deterioration and order backlogging under two financial schemes of progressive trade credit periods. We take both the continuous payment regime (CPR) and discrete payment regime (DPR) into account in the progressive trading process, which generates ten distinct scenarios. We show that the profit functions may not necessarily be concave and accordingly give a corresponding computing algorithm, which relaxes the convexity assumptions of objective functions in the existing literature and consequently enrich the research. We address the formulation characterization and the logic of pursuing global optimization from models arising in all settings. Computational studies and simulations are conducted to illustrate the effect of various parameters on the optimal replenishing policy and profit. Numerical experiments show that the CPR scheme is dominantly prior to DPR for long replenishment time intervals, whereas it is exactly the opposite for short time intervals. We also examine the impact of the shortage cost and deteriorating rate on optimum ordering policy and channel performance. Finally, future research directions are addressed in the end.