Variable Neighborhood Genetic Algorithm for the Flexible Job Shop Scheduling Problems
نویسندگان
چکیده
Flexible job shop scheduling problem (FJSP) is an important extension of the classical job shop scheduling problem, where the same operation could be processed on more than one machine. A Variable Neighborhood Genetic Algorithm (VNGA) is proposed for the problem with makespan criterion, consisting of a combination of the variable neighborhood search (VNS) and genetic algorithm (GA). Variable neighborhood search is adopted to improve the quality of individuals of GA before injecting them into the population and strengthen the local search ability. Two different neighborhood structures are used in the VNS. Representative flexible job shop scheduling benchmark problems are solved using the VNGA. Computational results show that the proposed algorithm is efficient and effective.
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Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model
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