Management Science and Financial Engineering
- 제3권2호
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- Pages.29-43
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- 1997
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- 2287-2043(pISSN)
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- 2287-2361(eISSN)
DYNAMIC SELECTION OF DISPATCHING RULES BY ARTIFICIAL NEURAL NETWORKS
초록
Many heuristics have been developed in order to overcome the computational complexity of job shop problems. In this research, we develop a new heuristic by selecting four simple dispatching rules, i.e., SPT, LPT, SR and LR, dynamically as scheduling proceeds. The selection is accomplished by using artificial neural networks. As a result of testing on 50 problems, the makespan obtained by our heuristic is, on the average, 13.0% shorter than the longest makespan, and 0.4% shorter than the shortest makespan obtained by existing dispatching rules.
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