Evaluation of a Postponement System with an (r, q) Policy

T.C. Edwin Cheng (), Jian Li (), C.L. Johnny Wan () and Shouyang Wang ()
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T.C. Edwin Cheng: The Hong Kong Polytechnic University
Jian Li: School of Economics & Management Beijing University of Chemical Technology (BUCT)
C.L. Johnny Wan: The Hong Kong Polytechnic University
Shouyang Wang: Chinese Academy of Sciences Academy of Mathematics & Systems Science

Chapter Chapter 4 in Postponement Strategies in Supply Chain Management, 2010, pp 81-108 from Springer

Abstract: In this chapter we study the cost impact of the pull postponementpull postponement strategy by comparing the total average cost function with the optimal or an approximately optimal total average cost of an ( $$r, q$$ ) policy. This is a stochastic model stochastic models of a single end-product supply chainsupply chain that consists of a supplier, a manufacturer and a number of customers. We develop two distinct models to represent the inventory system of the manufacturer. We employ Markov chainMarkov chain analysis to determine the exact average inventory level and the exact average accumulated backorder per period at the steady state so that the total average cost can be evaluated analytically. Also, we design an algorithm to find a near optimal total average cost per period. Our results show that the postponement systempostponement system is more cost effective when the lead-timelead-time is zero, while the ( $$r, q$$ ) inventory system is more effective when the lead-timelead-time is greater than zero.

Date: 2010
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DOI: 10.1007/978-1-4419-5837-2_4

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