Multistage supply chain production-inventory model with collaborative preservation technology investment

This paper investigates a multistage production-inventory model for deteriorating items, including raw materials and finished goods, based on collaborative preservation technology investment. The major purpose is to determine the optimal materials supply, production delivery, replenishment, and investment policies for the retailer and manufacturer in which the joint total profit of the integrated system is maximized. Mathematical programming analysis is employed to ascertain the optimal solutions for the retailer and manufacturer. Furthermore, several numerical examples are presented to demonstrate solution process and verify the concavity of the proposed model. Sensitivity analyses with respect to major parameters are also performed. The numerical results show that market demand, fixed shipping cost, production rate, manufacturer's sales price, and holding cost of finished good may affect the optimal number of shipments. In addition, when collaborative preservation technology investment becomes an option, the effect of the deterioration rate on the shipping and ordering quantity will be reduced through investment in improving deterioration of raw material or finished good. Finally, the increase in the amount of raw materials used to produce a finished product implies that the amount of finished goods produced by the original material is reduced; therefore, the collaborative preservation technology investment is increased. (C) 2022 Sharif University of Technology. All rights reserved.

Automated summary

This paper investigates a multistage production-inventory model for deteriorating items and examines the optimal strategies for the retailer and manufacturer based on collaborative preservation technology investment, aiming to maximize the total profit of the integrated system. Mathematical programming analysis is employed to determine the optimal solutions, and numerical examples are presented to illustrate the solution process and verify the concavity of the proposed model. Sensitivity analyses are conducted to examine the impact of major parameters on the optimal number of shipments.