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Optimal Control of Decoupling Point with Deteriorating Items

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DOI: 
http://dx.doi.org/10.3926/jiem.1205
Abstract (2. Language): 
Purpose: The aim of this paper is to develop a dynamic model to simultaneously determine the optimal position of the decoupling point and the optimal path of the production rate as well as the inventory level in a supply chain. With the objective to minimize the total cost of the deviation from the target setting, the closed forms of the optimal solution are derived over a finite planning horizon with deterioration rate under time-varying demand rate. Design/methodology/approach: The Pontryagin's Maximum Principle is employed to explore the optimal position of decoupling point and the optimal production and inventory rate for the proposed dynamic models. The performances of parameters are illustrated through analytical and numerical approaches. Findings: The results denote that the optimal production rate and inventory level are closely related to the target setting which are highly dependent on production policy; meanwhile the optimal decoupling point is exist and unique with the fluctuating of deteriorating rate and product life cycle. The further analyses through both mathematic and numerical approaches indicate that the shorten of product life cycle shifts the optimal decoupling point forward to the end customer meanwhile a backward shifting appears when the deterioration rate increase. Research limitations/implications: There is no shortage allowed and the replacement policy is not taken into account. Practical implications: Solutions derived from this study of the optimal production-inventory plan and decoupling point are instructive for operation decision making. The obtained knowledge about the performance of different parameters is critical to deteriorating supply chains management. Originality/value: Many previous models of the production-inventory problem are only focused on the cost. The paper introduces the decoupling point control into the production and inventory problem such that a critical element—customer demand, can be taken into account. And the problem is solved as dynamic when the production rate, inventory level and the position of the decoupling point are all regarded as decision variables.
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REFERENCES

References: 

Agarwal, A., Shankar, R., & Tiwari, M.K. (2006). Modeling the metrics of lean, agile and leagile
supply chain: An ANP-based approach. European Journal of Operational Research, 173(1),
211-225. http://dx.doi.org/10.1016/j.ejor.2004.12.005
Balkhi, Z.T., & Benkherouf, L. (2004). On an inventory model for deteriorating items with stock
dependent and time-varying demand rates. Computers and Operations Research, 31(2),
223-240. http://dx.doi.org/10.1016/S0305-0548(02)00182-X
Baten, A., & Kamil, A.A. (2009). Analysis of inventory-production systems with Weibull
distributed deterioration. International Journal of Physical Sciences, 4(11), 676-682.
http://dx.doi.org/10.1016/j.ijps. ED8434F19782
Ben Naylor, J., Naim, M.M., & Berry, D. (1999). Leagility: integrating the lean and agile
manufacturing paradigms in the total supply chain. International Journal of production
economics, 62(1), 107-118. http://dx.doi.org/10.1016/S0925-5273(98)00223-0
Benhadid, Y., Tadj, L., & Bounkhel, M. (2008). Optimal control of production inventory systems
with deteriorating items and dynamic costs. Applied Mathematics E-Notes, 8, 194-202.
http://dx.doi.org/10.1016/j.amen.2008.07.031
Cheng, M., & Wang, G. (2009). A note on the inventory model for deteriorating items with
trapezoidal type demand rate. Computers & Industrial Engineering, 56(4), 1296-1300.
http://dx.doi.org/10.1016/j.cie.2008.07.020
Choi. J., Realff, M.J., & Lee, J.H. (2005). Stochastic Dynamic Programming with Localized Costto-
go Approximators: Application to large scale supply chain management under demand
uncertainty. Chemical Engineering Research and Design, 83(6), 752-758.
http://dx.doi.org/10.1205/cherd.04375
Emamverdi, G.A., Karimi, M.S., & Shafiee, M. (2011). Application of Optimal Control Theory to
Adjust the Production Rate of Deteriorating Inventory System (Case Study: Dineh Iran Co.).
Middle-East Journal of Scientific Research, 10(4), 526-531. http://dx.doi.org/10.1016/j.mesr.10.27.02
Ghare, P.M., & Schrader, G.F. (1963). A model for exponentially decaying inventory. Journal of
Industrial Engineering, 14(5), 238-243.
Gupta, D., & Benjaafar, S. (2004). Make-to-order, make-to-stock, or delay product
differentiation? A common framework for modeling and analysis. IIE transactions, 36(6),
529-546. http://dx.doi.org/10.1080/07408170490438519
Hoekstra, S., Romme, J., & Argelo, S.M. (1992). Integral Logistic Structures: Developing
Customer-Oriented Goods Flow. New York: McGraw-Hill Book Co Ltd.
Hsu, P.H., Wee, H.M., & Teng, H.M. (2007). Optimal ordering decision for deteriorating items
with expiration date and uncertain lead-time. Computers and Industrial Engineering, 52(4),
448-458. http://dx.doi.org/10.1016/j.cie.2007.02.002
Jeong, I.J. (2011). A dynamic model for the optimization of decoupling point and production
planning in a supply chain. International Journal of Production Economics, 131(2), 561-567.
http://dx.doi.org/10.1016/j.ijpe.2011.02.001
Kamien, M.I., & Schwartz, N.L. (2012). Dynamic optimization: the calculus of variations and
optimal control in economics and management. New York: Courier Dover Publications.\
Li, R., Lan, H., & Mawhinney, J.R. (2010). A review on deteriorating inventory study. Journal of
Service Science and Management, 3(1), 117. http://dx.doi.org/10.4236/jssm.2010.31015
Olhager, J. (2003). Strategic positioning of the order penetration point. International Journal of
Production Economics, 85(3), 319-329. http://dx.doi.org/10.1016/S0925-5273(03)00119-1
Pontryagin, L.S. (1987). Mathematical Theory of Optimal Processes. Florida: CRC Press.
Porter, B., & Taylor, F. (1972). Modal control of production-inventory systems. International
Journal of Systems Science, 3(3), 325-331. http://dx.doi.org/10.1080/00207727208920270
Riddalls, C.E., & Bennett, S. (2001). The optimal control of batched production and its effect
on demand amplification. International Journal of Production Economics, 72(2), 159-168.
http://dx.doi.org/10.1016/S0925-5273(00)00092-X
Sarkar, B. (2013). A production-inventory model with probabilistic deterioration in two-echelon
supply chain management. Applied Mathematical Modeling, 37, 3138-3151.
http://dx.doi.org/10.1016/j.apm.2012.07.026
Soman, C.A., Van Donk, D.P., & Gaalman, G. (2004). Combined make-to-order and
make-to-stock in a food production system. International Journal of Production Economics,
90(2), 223-235. http://dx.doi.org/10.1016/S0925-5273(02)00376-6
Van Donk, D.P. (2001). Make to stock or make to order: The decoupling point in the food
processing industries. International Journal of Production Economics, 69, 297-306.
http://dx.doi.org/10.1016/S0925-5273(00)00035-9
Viswanadham, N., & Raghavan, N.R.S. (2000). Performance analysis and design of supply
chains: a Petri net approach. Journal of the Operational Research Society, 51, 1158–1169.
http://dx.doi.org/10.2307/253928
Wang, K.J., Lin Y.S., & Yu J.C.P. (2011). Optimizing inventory policy for products with timesensitive
deteriorating rates in a multi-echelon supply chain. International Journal of
Production Economics, 130, 66–76. http://dx.doi.org/10.1016/j.ijpe.2010.11.009

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