Climbing depth-bounded adjacent discrepancy search for solving hybrid flow shop scheduling problems with multiprocessor tasks

Authors:
Asma Lahimer;Pierre Lopez;Mohamed Haouari
Affiliations:
CNRS, LAAS, Université de Toulouse, UPS, INSA, INP, ISAE, UT1, UTM, LAAS, Toulouse Cedex, France;CNRS, LAAS, Université de Toulouse, UPS, INSA, INP, ISAE, UT1, UTM, LAAS, Toulouse Cedex, France;INSAT, Institut National des Sciences Appliquées et de Technologie, Tunis Cedex, Tunisie
Venue:
CPAIOR'11 Proceedings of the 8th international conference on Integration of AI and OR techniques in constraint programming for combinatorial optimization problems
Year:
2011

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Abstract

This paper considers multiprocessor task scheduling in a multistage hybrid flow-shop environment. The problem even in its simplest form is NP-hard in the strong sense. The great deal of interest for this problem, besides its theoretical complexity, is animated by needs of various manufacturing and computing systems. We propose a new approach based on limited discrepancy search to solve the problem. Our method is tested with reference to a proposed lower bound as well as the best-known solutions in literature. Computational results show that the developed approach is efficient in particular for large-size problems.