Hybrid Heuristic Approaches for Scheduling in Reconfigurable Manufacturing Systems

Reconfigurable Manufacturing Systems (RMS) are the next step in manufacturing, allowing the production of any quantity of highly customized products together with the benefits of mass production. In RMS, products are grouped into families, each of which requires one configuration of the system. The system is configured for producing the first family of products. Once it is finished, the system is reconfigured in order to produce the second family, and so forth. Then, the effectiveness of a RMS depends on the selection of the best set of product families and their scheduling. A methodology has been developed to group products into families, which takes into account the requirements of products in RMS. Once the families have been selected, a model to optimize the production scheduling is presented. This model is based on minimizing the costs required to reconfigure the system while both the capacity and functionality of machines are maximized. The complexity of the problem suggests the use of heuristics methodologies. Several heuristics are candidates to be used. With the aim of covering different approaches, both a specific heuristic for this problem and general heuristics or meta-heuristics have been developed. Tabu search is a traditional meta-heuristic that has demonstrated to offer satisfactory results to a broad range of combinatorial problems, and it has been considered to be implemented. In order to use another meta-heuristic to compare results, ant colony optimization techniques have been implemented because they have demonstrated to offer good behaviors to similar problems.

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