Integrating Customer Order Decoupling Point with Operation Planning in Deteriorating Supply Chain: General Dynamic Model and Applications

Ermei Wang (), Lin Li (), Kuan Yang and Yinggao Zhou ()
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Ermei Wang: Business School of Hunan University, School of Economics and Management, Hunan University of Arts and Science, Changsha 410082, P. R. China
Lin Li: Business School of Hunan University, Changsha 410082, P. R. China
Kuan Yang: Business School of Hunan University, Changsha 410082, P. R. China
Yinggao Zhou: School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China

Asia-Pacific Journal of Operational Research (APJOR), 2023, vol. 40, issue 02, 1-27

Abstract: Considering the real dilemma of deteriorating items, we explore how to find a balance between the conflicting achievements of enhancing flexibility and reducing costs. We propose a general dynamic model to penetrate customer orders by decoupling point with objective to minimize the cost. The closed forms of optimal solutions are obtained for companies to deal with the integrated problem of customer order decoupling point (CODP) decision and production–inventory plan simultaneously. Applications and numerical experiments are performed to illustrate practical insights for managers. The results show that the truth of zero-inventory policy is to avoid unnecessary inventory instead of absolutely no inventory. The CODP will shift forward with the increasing of customer demand rate and shift backward with the increasing of deterioration rate under the production smoothing policy. However, although it encounters the same changes of demand, the CODP moves with a smaller extent in high deterioration rate than in low. In addition, we find that during the growth phase of product life cycle, the increase of time-sensitive degree of demand is coupled with forward shifting of CODP; while during the decline phase, it is coupled with CODP backward shifting.

Keywords: CODP; operation scheduling; flexibility; cost efficiency; deteriorating items; time-varying demand (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1142/S021759592250021X

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