The overall aim of this study is to show that there is a critical interface between the lot sizing and tool management decisions, and these two problems cannot be viewed in isolation. We propose "ve alternative algorithms to solve lot sizing, tool allocation and machining conditions optimization problems simultaneously. The "rst algorithm is an exact algorithm which "nds the global optimum solution, and the others are heuristics equipped with a look-ahead mechanism to guarantee at least local optimality. The computational results indicate that the amount of improvement is statistically signi"cant for a set of randomly generated problems. The magnitude of cost savings is dependent on the system parameters. Scope and purpose In most of the studies on tool management, lot sizes are taken as a predetermined input while deciding on tool allocations and machining parameters. This might create empty feasible solution spaces and otherwise unnecessarily limit the number of ...
M. Selim Akturk, Siraceddin Onen