AccScience Publishing / IJOCTA / Volume 12 / Issue 1 / DOI: 10.11121/ijocta.2022.1034
RESEARCH ARTICLE

Analysis of make-to-stock queues with general processing times and startup and lost sales costs

Sinem Özkan1* Önder Bulut1
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1 Department of Industrial Engineering, Yaşar University, Turkey
IJOCTA 2022, 12(1), 8–19; https://doi.org/10.11121/ijocta.2022.1034
Received: 19 October 2020 | Accepted: 7 October 2021 | Published online: 23 October 2021
© 2021 by the Author(s). This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution -Noncommercial 4.0 International License (CC-by the license) ( https://creativecommons.org/licenses/by-nc/4.0/ )
Abstract

We consider a make-to-stock environment with a single production unit that  corresponds to a single machine or a line. Production and hence inventory are  controlled by the two-critical-number policy. Production times are independent  and identically distributed general random variables and demands are generated  according to a stationary Poisson process. We model this production-inventory  system as an M/G/1 make-to-stock queue. The main contribution of the study is to  extend the control of make-to-stock literature by considering general production  times, lost sales and fixed production costs at the same time. We characterize the  long-run behaviour of the system and also propose a simple but very effective  approximation to calculate the control parameters of the two-critical-number  policy. An extensive numerical study exhibits the effects of the production time  distribution and the system parameters on the policy control levels and average  system cost

Keywords
Production
Make-to-stock
Production and inventory control
Queueing theory
Renewal theory
Conflict of interest
The authors declare they have no competing interests.
References

[1] Gavish, B., Graves, S.C., (1980). A one-product  production/inventory problem under continuous  review policy. Operations Research, 28(5), 1228- 1236.

[2] Gavish, B., Graves, S.C., (1981).  Production/inventory systems with a stochastic  production rate under a continuous review policy.  Computers & Operations Research, 8(3), 169-183.

[3] Lee, H.S. Srinivasan, M.M., (1987). The continuous  review (s, S) policy for production/inventory systemswith Poisson demands and arbitrary processing  times. Technical Report, 87-33. 

[4] Graves, S.C., Keilson, J., (1981). The compensation  method applied to a one-product  production/inventory problem. Mathematics of  Operations Research, 6(2), 246-262.

[5] Srinivasan, M.M., Lee, H.S., (1991). Random  review production/inventory systems with  compound Poisson demands and arbitrary  processing times. Management Science, 37(7), 813- 833.

[6] Altiok, T., (1989). (R, r) production/inventory  systems. Operations Research, 37(2), 266-276.

[7] Tijms, H.C., (1980). An algorithm for average costs  denumerable state semi-Markov decision problems  with application to controlled production and  queueing system. In R. Hartley, L. C. Thomas, & D.  J. White, Recent developments in Markov decision  processes (pp. 143-179), Academic Press. 

[8] Heyman, D. P., (1968). Optimal operating policies  for M/G/1 queuing systems. Operations Research,  16(2), 362-382.

[9] Sobel, M.J., (1969). Optimal average-cost policy for  a queue with start-up and shut-down costs.  Operations research, 17(1), 145-162. 

[10] De Kok, A.G., Tijms, H.C., Van der Duyn Schouten,  F.A., (1984). Approximations for the single-product  production-inventory problem with compound  Poisson demand and service-level constraints.  Advances in Applied Probability, 16(2), 378-401.

[11] De Kok, A.G., (1985). Approximations for a lostsales production/inventory control model with  service level constraints. Management Science,  31(6), 729-737.

[12] De Kok, A.G., Tijms, H.C., (1985). A stochastic  production/inventory system with all-or-nothing  demand and service measures. Communications in  Statistics. Stochastic Models, 1(2), 171-190.

[13] De Kok, A.G., (1987). Approximations for operating  characteristics in a production-inventory model with  variable production rate. European journal of  operational research, 29(3), 286-297.

[14] Lin, H.J., (2017). Two-critical-number control  policy for a stochastic production inventory system  with partial backlogging. International Journal of  Production Research, 55(14), 4123-4135.

[15] Ha, A.Y., (1997a). Inventory rationing in a make-tostock production system with several demand  classes and lost sales. Management Science, 43(8),  1093-1103.

[16] Bulut, Ö., Fadiloğlu, M.M., (2011). Production  control and stock rationing for a make-to-stock  system with parallel production channels. IIE  Transactions, 43(6), 432-450.

[17] Özkan, S., Bulut, Ö. (2020). Control of make-tostock production systems with setup costs. Journal  of the Faculty of Engineering and Architecture of  Gazi University, 35(3), 1199-1212.

[18] Ha, A.Y., (1997b). Stock‐rationing policy for a  make‐to‐stock production system with two priority  classes and backordering. Naval Research Logistics(NRL), 44(5), 457-472.

[19] De Véricourt, F., Karaesmen, F., Dallery, Y., (2002).  Optimal stock allocation for a capacitated supply  system. Management Science, 48(11), 1486-1501.

[20] Ha, A.Y., (2000). Stock rationing in an M/Ek/1  make-to-stock queue. Management Science, 46(1),  77-87. 

[21] Gayon, J.P., De Vericourt, F., Karaesmen, F.,  (2009). Stock rationing in an M/Er/1 multi-class  make-to-stock queue with backorders. IIE  Transactions, 41(12), 1096-1109.

[22] Pang, Z., Shen, H., Cheng, T.C.E., (2014). Inventory  Rationing in a Make‐to‐Stock System with Batch  Production and Lost Sales. Production and  Operations Management, 23(7), 1243-1257.

[23] Yücel, Ö., Bulut, Ö., (2019). Control of M/Cox-2/s  make-to-stock systems. An International Journal of  Optimization and Control: Theories & Applications  (IJOCTA), 10(1), 26-36.

[24] Pervin, M., Roy, S.K., Weber, G.W. (2018).  Analysis of inventory control model with shortage  under time-dependent demand and time-varying  holding cost including stochastic deterioration.  Annals of Operations Research, 260(1), 437-460.

[25] Tirkolaee, E.B., Goli, A., Weber, G.W. (2019).  Multi-objective aggregate production planning  model considering overtime and outsourcing options  under fuzzy seasonal demand. In International  Scientific-Technical Conference Manufacturing,  (pp. 81-96). Springer, Cham.

[26] Lotfi, R., Weber, G.W., Sajadifar, S.M., Mardani, N.  (2020). Interdependent demand in the two-period  newsvendor problem. Journal of Industrial &  Management Optimization, 16(1), 117-140.

[27] Paksoy, T., Özceylan, E., Weber, G.W. (2010). A  multi objective model for optimization of a green  supply chain network. In AIP conference  proceedings (Vol. 1239, No. 1, pp. 311-320).  American Institute of Physics.

[28] Bose, S. K. (2002). Basic Queueing Theory. In An  Introduction to Queueing Systems (pp. 9-54).  Springer, Boston, MA.

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An International Journal of Optimization and Control: Theories & Applications, Electronic ISSN: 2146-5703 Print ISSN: 2146-0957, Published by AccScience Publishing