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A genetic algorithm to minimize maximum lateness on a batch processing machine
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DOI：10.1016/S0305-0548(01)00031-4.png)
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Abstract
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We consider the problem of minimizing maximum lateness on a batch processing machine in the presence of dynamic job arrivals. The batch processing machine can process up to B jobs simultaneously, and the processing time of a batch is given by that of the job with the longest processing time in the batch. We adapt a dynamic programming algorithm from the literature to determine whether a due-date feasible batching exists for a given job sequence. We then combine this algorithm with a random keys encoding scheme to develop a genetic algorithm for this problem. Computational experiments indicate that this algorithm has excellent average performance with reasonable computational burden.
Keywords:
scheduling
batch processing machines
dynamic programming
heuristics
genetic algorithms
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