Extended model formulation of the Proportional Lot-sizing and Scheduling Problem with lost demand costs

• Autorzy: Kaczmarczyk W.
• Języki publikacji: EN

Abstrakty

EN

We consider mixed-integer linear programming (MIP) models of production planning problems known as the small bucket lot-sizing and scheduling problems. We present an application of a class of valid inequalities to the case with lost demand (stock-out) costs. Presented results of numerical experiments made for the the Proportional Lot-sizing and Scheduling Problem (PLSP) confirm benefits of such extended model formulation.

Słowa kluczowe

EN

production; lot-sizing; scheduling; mixed integer linear programming

• Wydawca: AGH University of Science and Technology Press
• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2011
• Tom: Vol. 5, no. 1-2
• Strony: 49--56
• Opis fizyczny: Bibliogr. [21] poz., tab.

Twórcy

autor

Kaczmarczyk W.

• AGH University of Science and Technology, Faculty of Management, Department of Operations Research and Information Technology, Krakow, Poland

Bibliografia

• Absi, N., Kedad-Sidhoum, S., 2008. The multi-item capacitated lot-sizing problem with setup times and shortage costs. European Journal of Operational Research 185, 1351–1374.
• Aksen, D., 2007. Loss of customer goodwill in the uncapacitated lot-sizing problem. Computers & Operations Research 34, 2805–2823.
• Aksen, D., Altınkemer, K., Chand, S., 2003. The single-item lot-sizing problem with immediate lost sales. European Journal of Operational Research 147, 558–566.
• Barany, I., van Roy, T. J., 1984. Uncapacitated lot-sizing: The convex hull of solutions. Mathematical Programming Studies 22, 32–43.
• Belvaux, G., Wolsey, L.A., 2001. Modelling practical lot-sizing problems as mixed-integer programs. Management Science 47(7), 993–1007.
• Berk, E., Toy, A. O., Hazır, O., 2008. Single item lot-sizing problem for a warm/cold process with immediate lost sales. European Journal of Operational Research 187, 1251–1267.
• Drexl, A., Haase, K., 1995. Proportional lotsizing and scheduling. International Journal of Production Economics 40, 73–87.
• Drexl, A., Kimms, A., 1997. Lot sizing and scheduling – survey and extensions. European Journal of Operational Research 99(2), 221–235.
• Haase, K., 1994. Lotsizing and scheduling for production planning. In Lecture Notes in Economics and Mathematical Systems, number 408, Springer-Verlag.
• Jans, R., Degraeve, Z., 2008. Modeling industrial lot sizing problems: a review. International Journal of Production Research 46(6), 1619–1643.
• Kaczmarczyk, W., 2009a. Modelling multi-period set-up times in the proportional lot-sizing problem. Decision Making in Manufacturing and Services 3(1–2), 15–35.
• Kaczmarczyk, W., 2009b. Practical Tips for Modelling Lot-Sizing and Scheduling Problems. Decision Making in Manufacturing and Services 3, 37–48.
• Kaczmarczyk, W., 2011. Proportional lot-sizing and scheduling problem with identical parallel machines. International Journal of Production Research 49(9), 2605–2623.
• Liu, X., Chu, F., Chu, C., Wang C., 2007. Lot sizing with bounded inventory and lost sales. International Journal of Production Research 45(24), 5881–5894.
• Loparic, M., Pochet Y., Wolsey, L. A., 2001. The uncapacitated lot-sizing problem with sales and safety stocks. Mathematical Programming 89, 487–504.
• Lu, L., Qi, X., 2011. Dynamic lot sizing for multiple products with a new joint replenishment model. European Journal of Operational Research 212, 74–80.
• Pochet, Y., Wolsey, L.A., 2006. Production planning by mixed integer programming. Series in Operations Research and Financial Engineering, Springer. New York.
• Sandbothe, R. A., Thompson, G. L., 1990. A Forward Algorithm For The Capacitated Lot Size Model With Stockouts. Operations Research 38(3), 474–486.
• Suerie, C., 2005. Time Continuity in Discrete Time Models, Springer.
• Wagner, H.M., Whitin, T.M., 1958. Dynamic version of the economic lot size model. Management Science 5, 89–96.
• Wolsey, L. A., 2002. Solving multi-item lot-sizing problems with an MIP solver using classification and reformulation. Management Science 48(12), 1587–1602.