A hybrid genetic heuristic for scheduling parallel batch processing machines with arbitrary job sizes |
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Authors: | Ali Husseinzadeh Kashan Behrooz KarimiMasoud Jenabi |
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Affiliation: | Department of Industrial Engineering, Amirkabir University of Technology, 424 Hafez Ave., Tehran 15916-34311, Iran |
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Abstract: | This paper investigates the scheduling problem of parallel identical batch processing machines in which each machine can process a group of jobs simultaneously as a batch. Each job is characterized by its size and processing time. The processing time of a batch is given by the longest processing time among all jobs in the batch. Based on developing heuristic approaches, we proposed a hybrid genetic heuristic (HGH) to minimize makespan objective. To verify the performance of our algorithm, comparisons are made through using a simulated annealing (SA) approach addressed in the literature as a comparator algorithm. Computational experiments reveal that affording the knowledge of problem through using heuristic procedures, gives HGH the ability of finding optimal or near optimal solutions in a reasonable time. |
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Keywords: | Scheduling Parallel batch processing machines Genetic algorithm Simulated annealing |
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