Abstract
This article studies a single item dynamic lot sizing problem with manufacturing and remanufacturing provisions. The demands and returns are considered as both stochastic and deterministic. There are two inventories recoverable and serviceable inventory. We developed a dynamic programming based model with objective to determine the quantities that have to be manufactured or re-manufactured at each period in order to minimize the total cost, including production cost, holding cost for returns and finished goods, and backlog cost. Also, unit production cost is also taken as variable in case of deterministic case. Finally, a numerical example for each of deterministic and stochastic model is worked out to illustrate how the model is applied and to prove its feasibility.
Similar content being viewed by others
References
Baker K. B., Dixon P., Magazine M. J. (1978) An algorithm for the dynamic lot-size problem with time-varyingproduction capacity constraints. Management Science 24(16): 1710–1720
Beltran J. L., Krass D. (2002) Dynamic lot sizing with returning items and disposals. IIE Transactions 34: 437–448
Driesch, H. M., Van Oyen, H., & Flapper, S. (2001). Recovery of car engines: The Mercedes-Benz case study.
Fleischmann M., Bloemhof-Ruwaard J. M., Dekker R., van der Laan E., van Nunen J. A. E. E., van Wassenhove L. N. (1997) Quantitative models for reverse logistics: A review. European Journal of Operational Research 103: 1–17
Florian M., Klein M. (1971) Deterministic production planning with concave costs and capacity constraints. Management Science 18(1): 12–20
Golany B., Yang J., Yu G. (2001) Economic lot-sizing with remanufacturing options. IIE Transactions 33: 995–1003
Kelle P., Silver E. A. (1989) Purchasing policy of new containers considering the random returns of previously issued containers. IIE Transactions 21: 349–354
Koh S., Hwang H., Sohn K., Ko C. (2002) An optimal ordering and recovery policy for reusable items. Computers and Industrial Engineering 43(1-2): 59–73
Li C., Liu F., Cao Q. (2009) A stochastic dynamic programming based model for uncertain production planning of re-manufacturing system. International Journal of Production Research 47(13): 3657–3668
Oh Y. H., Hwang H. (2006) Deterministic inventory model for recycling system. Journal of Intelligent Manufacturing 17(4): 423–428
Raa B., Aghezzaf E. H. (2005) A robust dynamic planning strategy for lot-sizing problems with stochastic demands. Journal of Intelligent Manufacturing 16(2): 207–213
Richter K., Sombrutzki M. (2000) Remanufacturing planning for the reverse Wagner/Whitin models. European Journal of Operational Research 121: 304–315
Richter K., Weber J. (2001) The reverse Wagner/Whitin model with variable manufacturing and remanufacturing cost. International Journal of Production Economics 71: 447–456
Teunter R., Bayindir Z. P., van den Heuvel W. (2006) Dynamic lot sizing with product returns and remanufacturing. International Journal of Production Research 44(20): 4377–4400
Toktay L. B., Wein L. M., Zenios S. A. (2000) Inventory management of remanufacturable products. Management Science 46: 1412–1428
van der Laan E., Salomon M. (1997) Production planning and inventory control with remanufacturing and disposal. European Journal of Operational Research 102: 264–278
Wagner H. M., Whitin T. M. (1959) Dynamic version of the economic lot size model. Management Science 5(1): 89–96
Wang L., Tang D., Gu W., Zheng K., Yuan W., Tang D. (2009) Pheromone-based coordination for manufacturing system control. Journal of Intelligent Manufacturing 20(6): 671–682
Wei, C., Li, Y., & Cai, X. (2009). Robust optimal policies of production and inventory with uncertain returns and demand. International Journal of Production Economics (in press).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Naeem, M.A., Dias, D.J., Tibrewal, R. et al. Production planning optimization for manufacturing and remanufacturing system in stochastic environment. J Intell Manuf 24, 717–728 (2013). https://doi.org/10.1007/s10845-011-0619-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10845-011-0619-0