کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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414592 | 680987 | 2009 | 10 صفحه PDF | دانلود رایگان |

The operations of the semiconductor final test industry are complicated and characterized by multiple-resource constraints that require simultaneous considerations. One of the most challenging production-planning decisions in the industry concerns an efficient allocation of resources that results in high manufacturing performance. Firms in the industry are thus eager to discover resource-allocation knowledge from large manufacturing databases. This study develops a novel model via the extraction of fuzzy-business rules from databases for obtaining resource-allocation knowledge as well as allocating resources efficiently. The proposed model uses both a genetic algorithm to find the best priority sequence of customer orders for resource allocation and, in accordance with the priority sequence of orders, a fuzzy-inference model to allocate the resources and to determine the order-completion times. Experiments showed that the proposed model can significantly reduce task tardiness.
Journal: Robotics and Computer-Integrated Manufacturing - Volume 25, Issue 1, February 2009, Pages 32–41