IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A particle swarm optimization algorithm for flexible jobshop scheduling problem
CASE'09 Proceedings of the fifth annual IEEE international conference on Automation science and engineering
Short Communication: An effective TPA-based algorithm for job-shop scheduling problem
Expert Systems with Applications: An International Journal
Genetic algorithms for match-up rescheduling of the flexible manufacturing systems
Computers and Industrial Engineering
A SOMO-based approach to the operating room scheduling problem
Expert Systems with Applications: An International Journal
Computers and Operations Research
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In this paper, we propose a new hierarchical method for the flexible job-shop scheduling problem (FJSP). This approach is mainly adapted to a job-shop problem (JSP) with high flexibility and is based on the decomposition of the problem in an assignment subproblem and a sequencing subproblem. For the first subproblem, we propose two methods: the first one is based successively on a heuristic approach and a local search; the second one, however, is based on a branch-and-bound algorithm. The quality of the assignment is evaluated by a lower bound. For the second subproblem we apply a hybrid genetic algorithm to deal with the sequencing problem. Computational tests are finally presented.