Abstract
From an Al perspective, the job-shop is a constraint satisfaction problem (CSP), and many specific techniques have been developed to solve it efficiently. In this context, one may believe that generic search and CSP methods are not appropriated for this problem. In this paper, we contradict this belief. We show that generic search and CSP algorithms and heuristics can be successfully applied to job-shop problem instances that have been considered challenging by the job-shop community. In particular, we use forward checking with support-based heuristics, a combination of a generic CSP algorithm with generic heuristics. We improve this combination replacing the depth-first search strategy of forward checking by a discrepancy-based schema, a generic search strategy recently developed. Our approach obtains similar results to specific approaches in terms of the number of solved problems, with reasonable requirements in computational resources.
This research is supported by the Spanish CICYT project TIC96-0721-C02-02.
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© 1998 Springer-Verlag Berlin Heidelberg
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Larrosa, J., Meseguer, P. (1998). Generic CSP techniques for the job-shop problem. In: Pasqual del Pobil, A., Mira, J., Ali, M. (eds) Tasks and Methods in Applied Artificial Intelligence. IEA/AIE 1998. Lecture Notes in Computer Science, vol 1416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-64574-8_390
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DOI: https://doi.org/10.1007/3-540-64574-8_390
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