In this paper we introduce a genetic algorithm whose peculiarities are the introduction of an encoding based on preference rules and an updating step which speeds up the evolutionary process. This method improves on the results gained previously with Genetic Algorithms and has shown itself to be competitive with other heuristics. The same algorithm has been applied to flow shop problems, revealing itself to be considerably more effective than Branch and Bound techniques.

A genetic algorithm for the job shop problem / DELLA CROCE DI DOJOLA, Federico; Tadei, Roberto; G., Volta. - In: COMPUTERS & OPERATIONS RESEARCH. - ISSN 0305-0548. - 22:1(1995), pp. 15-24. [10.1016/0305-0548(93)E0015-L]

A genetic algorithm for the job shop problem

DELLA CROCE DI DOJOLA, Federico;TADEI, Roberto;
1995

Abstract

In this paper we introduce a genetic algorithm whose peculiarities are the introduction of an encoding based on preference rules and an updating step which speeds up the evolutionary process. This method improves on the results gained previously with Genetic Algorithms and has shown itself to be competitive with other heuristics. The same algorithm has been applied to flow shop problems, revealing itself to be considerably more effective than Branch and Bound techniques.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/1399384
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