A two-stage queueing network on form postponement supply chain with correlated demands

Abstract To ease the conflict between quick response and product variety, more and more business models are developed in supply chains. Among these, the form postponement (FP) strategy is an efficient tool and has been widely adopted. To the supply chain with FP strategy, the design mostly involves two problems: determination of customer order decoupling point (CODP) position and semi-finished product inventory control. In this paper, we develop a two-stage tandem queueing network with MAP arrival to address this issue. Particularly, we introduce a Markov arrival process (MAP) to characterize the correlation of the demand. By using of matrix geometric method, we derive several performance measure of the supply chain, such as inventory level and unfill rate. Our numerical examples show that both the variance and the correlation coefficient of the demand lead to more delayed CODP position and more total cost.

[1]  Sheldon M. Ross,et al.  Stochastic Processes , 2018, Gauge Integral Structures for Stochastic Calculus and Quantum Electrodynamics.

[2]  Christopher S. Tang,et al.  Modelling the Costs and Benefits of Delayed Product Differentiation , 1997 .

[3]  Awi Federgruen,et al.  Capacitated Multi-Item Inventory Systems with Random and Seasonally Fluctuating Demands: Implications for Postponement Strategies , 2001, Manag. Sci..

[4]  Diwakar Gupta,et al.  Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis , 2004 .

[5]  Awi Federgruen,et al.  Design for Postponement: A Comprehensive Characterization of Its Benefits Under Unknown Demand Distributions , 2001, Oper. Res..

[6]  Liming Liu,et al.  A tandem network with MAP inputs , 2008, Oper. Res. Lett..

[7]  Quan-Lin Li,et al.  Constructive Computation in Stochastic Models with Applications , 2010 .

[8]  L. P. Bucklin Postponement, Speculation and the Structure of Distribution Channels , 1965 .

[9]  S. Asmussen,et al.  Marked point processes as limits of Markovian arrival streams , 1993 .

[10]  Paul H. Zipkin,et al.  Foundations of Inventory Management , 2000 .

[11]  R. V. Hoek,et al.  The rediscovery of postponement a literature review and directions for research , 2001 .

[12]  Vaidyanathan Ramaswami,et al.  Introduction to Matrix Analytic Methods in Stochastic Modeling , 1999, ASA-SIAM Series on Statistics and Applied Mathematics.

[13]  Sameer Kumar,et al.  Effects of product postponement on the distribution network: a case study , 2009, J. Oper. Res. Soc..

[14]  W. D. Ray,et al.  Stochastic Models: An Algorithmic Approach , 1995 .

[15]  Mark Ferguson,et al.  Evaluation of postponement structures to accommodate mass customization , 2005 .

[16]  Hsu Guang-Hui,et al.  First passage times and their algorithms for Markov processes , 1995 .

[17]  Vidyadhar G. Kulkarni Introduction to matrix analytic methods in stochastic modeling, by G. Latouche and V. Ramaswamy , 1999 .

[18]  Attahiru Sule Alfa,et al.  A queueing model of delayed product differentiation , 2009, Eur. J. Oper. Res..

[19]  W. Zinn,et al.  PLANNING PHYSICAL DISTRIBUTION WITH THE PRINCIPLE OF POSTPONEMENT , 1988 .

[20]  Mohamed Mohamed Naim,et al.  Evaluation of postponement in the soluble coffee supply chain , 2011 .

[21]  R. Westbrook,et al.  Implications of Mass Customisation for Operations Management: An Exploratory Survey , 1999 .

[22]  N. D. Burns,et al.  Implications of postponement for the supply chain , 2003 .

[23]  Fabrizio Salvador,et al.  Operationalising form postponement from a decision-making perspective , 2011 .