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Title: Joint Production and Economic Retention Quantity Decision in Capacitated Production Systems Serving Multiple Market Segments
Authors: Babak Haji Karimi; Mohamad Mehdi Mozafari; Mehrdad Nazari Asli
DOI:
Aff: Department of management, Qazvin-Imam Khomeini International University, Qazvin, Iran.
Author Email: mehrdadnazariasli@yahoo.com
Keywords: Inventory Management; Economic Retention Quantity; Optimal Policy; Market
URLs: ABSTRACT-HTML  | FULLTEXT-PDF  | 
Abstract:In this research, we consider production/inventory management decisions of a firm that sells its product in two market segments during a finite planning horizon. In the beginning of each period, the firm makes a decision on how much to produce based on the production capacity and the current on-hand inventory available. After the production is made at the beginning of the period, the firm first satisfies the stochastic demand from customers in its primary market. Any primary market demand that cannot be satisfied is lost. After satisfying the demand from the primary market, if there is still inventory on hand, all or part of the remaining products can be sold in a secondary market with ample demand at a lower price. Hence, the second decision that the firm makes in each period is how much to sell in the secondary market, or equivalently, how much inventory to carry to the next period. The objective is to maximize the expected net revenue during a finite planning horizon by determining the optimal production quantity in each period, and the optimal inventory amount to carry to the next period after the sales in primary and secondary markets. We term the optimal inventory amount to be carried to the next period as \economic retention quantity". We model this problem as a finite horizon stochastic dynamic program. Our focus is to characterize the structure of the optimal policy and to analyze the system under different parameter settings. Conditioning on given parameter set, we establish lower and upper bounds on the optimal policy parameters. Furthermore, we provide computational tools to determine the optimal policy parameters. Results of the numerical analysis are used to provide further insights into the problem from a