Abstract

Manufacturing systems are often characterized by the use of resources which need to be 'renewed' after a period of use, such as tools and dies. The resources are not available during their maintenance and if it is too expensive to purchase a suitable number of copies, this may introduce delays and lower the quality of the schedule. We refer to such resources as delay-renewable . In the paper we consider a two-fold generalization of the classical job shop scheduling problem; the operations require the concurrent use of different resources (not only one machine) and the resources are delay-renewable. The resulting scheduling problem is obviously rather difficult and calls for suitable heuristics. A natural way to devise a heuristic approach is to decompose the overall problem into sub-problems and to exploit high-quality meta-heuristics, such as tabu search, for their solution. The purpose of the paper is to discuss and compare two decomposition approaches, differing in the way sub-problems interact, i.e. through constraints and/or information.

Full Text
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