Abstract
We consider a make-to-stock production/inventory model in a random environment with finite storage capacity and restricted backlogging possibility. Our aim is to demonstrate that all cost quantities of interest can be derived in closed form under quite general assumptions on the demand arrival process and on the switches in the production rates. Specifically, the demands arrive according to a Markov additive process governed by a continuous-time Markov chain, and their sizes are independent and have phase-type distributions depending on the type of arrival. The production process switches between predetermined rates which depend on the state of the environment and on the presence or absence of backlogs. Four types of costs are considered: the holding cost for the stock, the cost of lost production due to the finite storage capacity, the shortage cost for the backlogged demand and the cost due to unsatisfied demand. We obtain explicit formulas for these cost functionals in the discounted case and under the long-run average criterion. The derivations are based on optional sampling of a multi-dimensional martingale and on fluid flow techniques.









Similar content being viewed by others
References
Ahn, S., & Ramaswami, V. (2003). Fluid flow models and queues—a connection by stochastic coupling. Stochastic Models, 19, 325–348.
Ahn, S., & Ramaswami, V. (2004). Transient analysis of fluid models via stochastic coupling to a queue. Stochastic Models, 20, 71–101.
Ahn, S., & Ramaswami, V. (2005). Efficient algorithms for transient analysis of stochastic fluid flow models. Journal of Applied Probability, 42, 531–549.
Ahn, S., & Ramaswami, V. (2006). Transient analysis of fluid models via elementary level-crossing arguments. Stochastic Models, 22, 129–147.
Ahn, S., Badescu, L. A., & Ramaswami, V. (2007). Time dependent analysis of finite buffer fluid flows and risk models with a dividend barrier. Queueing Systems, 55, 207–222.
Asmussen, S. (2003). Applied probability and queues (2nd ed.). New York etc: Springer.
Asmussen, S., & Kella, O. (2000). A multi-dimensional martingale for Markov additive processes and its applications. Advances in Applied Probability, 32, 376–393.
Asmussen, S., & Albrecher, H. (2010). Ruin probabilities. Singapur: World Scientific.
Baek, J. W., Lee, H. W., Lee, S. W., & Ahn, S. (2011). A Markov modulated fluid flow queueing model under D-policy. Numerical linear algebra with applications, 18, 993–1010.
Barron, Y. (2014). A fluid EOQ model with Markovian environment. Journal of Applied Probability.
Barron, Y., Perry, D., & Stadje, W. (2014). A jump-fluid production-inventory model with a double band control. Probability in the Engineering and Informational Sciences.
Berman, O., Parlar, M., Perry, D., & Posner, M. J. M. (2005). Production/clearing models under continuous and sporadic review. Methodology and Computing in Applied Probability, 7, 203–224.
Cheung, E. C. K., & Landriault, D. (2010). A generalized penalty function with the maximum surplus prior to ruin in a MAP risk model. Insurance: Mathematics and Economics, 46, 127–134.
Doshi, B. T., Van Der Duyn Schouten, F. A., & Talman, A. J. J. (1978). A production inventory control model with a mixture of back-orders and lost-sales. Management Science, 24, 1078–1086.
Frostig, E. (2005). The expected time to ruin in a risk process with constant barrier via martingales. Insurance: Mathematics and Economics, 37, 216–228.
Katehakis, M. N., & Smit, L. C. (2012). On computing optimal (Q, r) replenishment policies under quantity discounts. Annals of Operations Research, 200(1), 279–298.
Kella, O., & Whitt, W. (1999). Useful Martingales for stochastic storage processes with Levy input. Journal of Applied Probability, 29, 396–403.
Kella, O., Perry, D., & Stadje, W. (2003). A stochastic clearing model with a Brownian and a compound Poisson component. Probability in the Engineering and Informational Sciences, 17, 1–22.
Kulkarni, V. G., & Yan, K. (2007). A fluid model with upward jumps at the boundary. Queueing Systems, 56, 103–117.
Kulkarni, V. G., & Yan, K. (2012). Production-inventory systems in stochastic environment and stochastic lead times. Queueing Systems, 70, 207–231.
Perry, D., Stadje, W., & Zacks, S. (1999). Contributions to the theory of first-exit times for some compound process in queueing theory. Queueing Systems, 33, 369–379.
Perry, D., Berg, M., & Posner, M. J. M. (2001). Stochastic models for broker inventory in dealership markets with a cash management interpretation. Insurance: Mathematics and Economics, 29, 23–34.
Perry, D., Stadje, W., & Zacks, S. (2005). Sporadic and continuous clearing policies for a production/inventory system under an M/G demand process. Mathematics of Operations Research, 30, 354–368.
Ramaswami, V. (2006). Passage times in fluid models with application to risk processes. Methodology and Computations in Applied Probability, 8, 497–515.
Shi, J., Katehakis, M. N., & Melamed, B. (2013). Martingale methods for pricing inventory penalties under continuous replenishment and compound renewal demands. Annals of Operations Research, 208(1), 593–612.
Shi, J., Katehakis, M.N., Melamed, B., & Xia, Y. (2014). Production-Inventory Systems with Lost-sales and Compound Poisson Demands. Operations Research, to be appear.
Yan, K., & Kulkarni, V. G. (2008). Optimal inventory policies under stochastic production and demand rates. Stochastic Models, 24, 173–190.
Author information
Authors and Affiliations
Corresponding author
Additional information
W. Stadje: Supported by Grant No. 306/13-2 of the Deutsche Forschungsgemeinschaft.
Rights and permissions
About this article
Cite this article
Barron, Y., Perry, D. & Stadje, W. A make-to-stock production/inventory model with MAP arrivals and phase-type demands. Ann Oper Res 241, 373–409 (2016). https://doi.org/10.1007/s10479-014-1679-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10479-014-1679-2