| Summary: | 碩士 === 國立臺灣科技大學 === 營建工程系 === 101 === Construction Industry uses various kinds of materials. To set suitable statistical sampling acceptance plans greatly impacts construction qualities. In statistical sampling acceptance plans, methods of attribute acceptance sampling plans are widely applicable. However, to identify suitable attribute acceptance sampling plans under settings of acceptance probabilities is the key to ensure construction qualities.
This research used a swarm intelligent algorithm, namely Roach Infestation Optimization (RIO), to calculate parameters of the attribute acceptance sampling plans including the numbers of samples, acceptances, and rejections under predefined risks of producers and customers. The resultant plans simultaneously aimed at two objectives, i.e. minimizing the total number of samples and the discrepancy among predefined risks and calculated risks. This research provided optimal results of single, double, and triple sampling acceptance plans. Various resultant plans were provided for project managers to face different needs and gave higher profits.
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