Stochastic production planning with internal and external storage and ordering costs

Jorge Luiz de Biazzi

doi:10.1590/1806-9649-2021v28e5790

Original Article

Stochastic production planning with internal and external storage and ordering costs

Jorge Luiz de Biazzi

http://dx.doi.org/10.1590/1806-9649-2021v28e5790 Gest. Prod., vol.28, n4, e5790, 2021

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Abstract

Abstract:: This paper aims to compare different models to support decision making in production planning (and, consequently, in sales and inventory), in an environment where product demands are variable and uncertain, it is possible to produce at normal hours and overtime, loss of sales is consequence of stockouts, there is limit to internal storage, with possible and more expensive external storage, and ordering costs are non-negligible. At first, we present a linear and deterministic model, with known demand and without shortage. In the second model, safety stocks are calculated to meet a probabilistic demand, but it is not yet considered the possibility of shortage. The third model includes shortage calculation as a consequence from demand uncertainty. The last two models use an iterative process to re-estimate the unit cost of storage, needed to calculate safety stocks in each period of the planning horizon. The models were implemented in MSExcel, making use of linear programming and search functions available in the software. As the original problem, data of the examples are based on real companies. The study allows concluding that, in the problem analyzed, linear models, simpler and faster to execute, may be sufficient to support good decisions.

Keywords

Sales and operations planning, Dynamic and probabilistic demand, Aggregate production planning, Non-negligible ordering costs

Referencias

Al-E-Hashem, S., Aryanezhad, M., & Sadjadi, S. (2012). An efficient algorithm to solve a multi-objective robust aggregate production planning in an uncertain environment. International Journal of Advanced Manufacturing Technology, 58(5), 765-782.

Biazzi, J. L. (2018). Aggregate planning for probabilistic demand with internal and external storage. Journal of Operations and Supply Chain Management, 11(1), 37-52. http://dx.doi.org/10.12660/joscmv11n1p37-52.

Bookbinder, J. H., & Tan, J. (1988). Strategies for the probabilistic lot-sizing problem with service-level constraints. Management Science, 34(9), 1096-1108. http://dx.doi.org/10.1287/mnsc.34.9.1096.

Buffa, E. S., & Sarin, R. K. (1987). Modern Production/Operations Management. (8th ed.). New York: Wiley.

Chopra, S., & Meindl, P. (2001). Supply Chain Management: strategy, planning and operation. New Jersey: Prentice-Hall.

Feiring, B. R., & Sastri, T. (1990). Improving production planning by utilizing stochastic programming. Computers & Industrial Engineering, 19(1-4), 53-56. http://dx.doi.org/10.1016/0360-8352(90)90076-X.

Günther, H. O. (1982). A comparison of two classes of aggregate production planning models under stochastic demand. Engineering Costs and Production Economics, 6, 89-97. http://dx.doi.org/10.1016/0167-188X(82)90042-8.

Helber, S., Sahling, F., & Schimmelpfeng, K. (2013). Dynamic capacitated lot sizing with random demand and dynamic safety stocks. OR-Spektrum, 35(1), 75-105. http://dx.doi.org/10.1007/s00291-012-0283-6.

Ketzenberg, M., Metters, R., & Semple, J. (2006). A heuristic for multi-item production with seasonal demand. IIE Transactions, 38(3), 201-211. http://dx.doi.org/10.1080/07408170500436096.

Lacerda, D. P., Dresch, A., Proença, A., & Antunes Júnior, J. A. V. (2013). Design Science Research: método de pesquisa para a engenharia de produção. Gestão & Produção, 20(4), 741-761. http://dx.doi.org/10.1590/S0104-530X2013005000014.

Lejeune, M. A., & Ruszczynski, A. (2007). An efficient trajectory method for probabilistic production-inventory-distribution problems. Operations Research, 55(2), 378-394. http://dx.doi.org/10.1287/opre.1060.0356.

Li, B., Wang, H., Yang, J., Guo, M., & Qi, C. (2013). A belief-rule-based inference method for aggregate production planning under uncertainty. International Journal of Production Research, 51(1), 83-105. http://dx.doi.org/10.1080/00207543.2011.652262.

Martínez-Costa, C., Mas-Machuca, M., Benedito, E., & Corominas, A. (2014). A review of mathematical programming models for strategic capacity planning in manufacturing. International Journal of Production Economics, 153, 66-85. http://dx.doi.org/10.1016/j.ijpe.2014.03.011.

Olhager, J., & Johansson, P. (2012). Linking long-term capacity management for manufacturing and service operations. Journal of Engineering and Technology Management, 29(1), 22-33. http://dx.doi.org/10.1016/j.jengtecman.2011.09.003.

Pauls-Worm, K. G. J., Hendrix, E. M. T., Alcoba, A. G., & Haijema, R. (2016). Order quantities for perishable inventory control with non-stationary demand and a fill rate constraint. International Journal of Production Economics, 181, 238-246. http://dx.doi.org/10.1016/j.ijpe.2015.10.009.

Silver, E. A., Pyke, D. F., & Peterson, R. (1998). Inventory Management and Production Planning and Scheduling. New York: Wiley.

Tarim, S. A., & Kingsman, B. G. (2004). The stochastic dynamic production/inventory lot-sizing problem with service-level constraints. International Journal of Production Economics, 88(1), 105-119. http://dx.doi.org/10.1016/S0925-5273(03)00182-8.

Tarim, S. A., & Kingsman, B. G. (2006). Modelling and computing (Rⁿ,Sⁿ) policies for inventory systems with non-stationary stochastic demand. European Journal of Operational Research, 174(1), 581-599. http://dx.doi.org/10.1016/j.ejor.2005.01.053.

Tenhiälä, A. (2011). Contingency theory of capacity planning: the link between process types and planning methods. Journal of Operations Management, 29(1-2), 65-77. http://dx.doi.org/10.1016/j.jom.2010.05.003.

Thomé, A. M. T., Scavarda, L. F., Fernandez, N. S., & Scavarda, A. J. (2012). Sales and operations planning: a research synthesis. International Journal of Production Economics, 138(1), 1-13. http://dx.doi.org/10.1016/j.ijpe.2011.11.027.

Stochastic production planning with internal and external storage and ordering costs

Jorge Luiz de Biazzi

Abstract

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