A fuzzy-knowledge resource-allocation model of the semiconductor final test industry
作者： Kung-Jeng Wang , Y.-S. Lin , Chen-Fu Chien , J.C. Chen
DOI: 10.1016/J.RCIM.2007.05.004
关键词:
摘要: The operations of the semiconductor final test industry are complicated and characterized by multiple-resource constraints that require simultaneous considerations. One most challenging production-planning decisions in concerns an efficient allocation resources results high manufacturing performance. Firms thus eager to discover resource-allocation knowledge from large databases. This study develops a novel model via extraction fuzzy-business rules databases for obtaining as well allocating efficiently. proposed uses both genetic algorithm find best priority sequence customer orders resource and, accordance with orders, fuzzy-inference allocate determine order-completion times. Experiments showed can significantly reduce task tardiness.
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