The Economic Lot-Sizing Problem: New Results and Extensions Defended on Thursday, 7 December 2006
One way for firms to reduce cost is efficient production planning. The main theme in this thesis is a classical production planning problem: the economic lot-sizing (ELS) problem. The objective of this problem is to find a production plan that satisfies the given demand for a finite, discrete planning horizon, and minimizes the total setup, production and holding costs. We study aspects of the classical problem as well as extensions of this problem. In the first part of the thesis we consider the ELS model with time-invariant cost parameters. We analyze properties of an optimal solution and, in particular, we are interested in the proportion of holding cost and setup cost in an optimal solution. Furthermore, we perform a worst case analysis on a broad class of on-line heuristics for the problem. Because the classical model is relatively simple, we also consider extensions of the model. We are interested whether there exist algorithms to solve the extensions efficiently. In the first extension we incorporate pricing decisions in the ELS model. The problem is now to find optimal price(s) and an optimal production plan simultaneously. We consider models with variable prices and a constant price over time. Furthermore, we extend the ELS model with a remanufacturing option. It is assumed that a known quantity of products returns from the customer in each period and those returned products can be remanufactured to satisfy demand (besides regular manufacturing). We derive algorithms and complexity results for models with a joint setup cost for manufacturing and remanufacturing (in case of a single production line) and a separate setup cost (in case of separate production lines).
Lot-sizing, Production Planning, Worst Case Analysis, Pricing, Remanufacturing, Dynamic Programming, Integrated Decisions
van den Heuvel, W. (2006, December 7). The Economic Lot-Sizing Problem: New Results and Extensions (No. 93). ERIM Ph.D. Series Research in Management. Erasmus Research Institute of Management. Retrieved from hdl.handle.net/1765/8193