Optimal Inventory-allocation Integrated Model for Perishable Items with Stochastic Demand in a Single-vendor Multi-retailer Supply Chain

This study investigates an increasingly widespread supply chain system that involves a vendor cyclically supplying specific perishable item to multiple retailers. In general, the vendor has to earlier and accurately determine inventory quantity to meet aggregate demand, and exactly allocate the inventory among a number of retailers to reduce the adjustment costs. Meanwhile, a vital challenge faced for vendors is to develop an efficient inventory- allocation decision model for given perishable item with stochastic and correlated retailer demands during upcoming selling period. To this end, an effective and practical analytical approach, which extends the newsvendor model to incorporate the considered inventory- allocation decision, is proposed here to simultaneously solve the optimal inventory quantity and allocation policy for maximizing expected vendor profits of perishable items. Especially, the lognormal distribution and Ito process is used here to model the behaviors of individual demand shift. Also, an effective integrated approach is presented to work out the aggre- gate demand during next selling period. Finally, numerical experiments are conducted to demonstrate and validate the proposed model and extract the valuable managerial findings.