Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry
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. H...
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ndltd-TW-101NTUS55120602019-08-04T03:37:27Z http://ndltd.ncl.edu.tw/handle/54yvth Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry 蟑螂演算法於營建工程計數型抽樣驗收計畫之研究 SU-MAN HU 胡素滿 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. Yong-Huang Lin 林耀煌 2013 學位論文 ; thesis 100 zh-TW |
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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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Yong-Huang Lin |
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Yong-Huang Lin SU-MAN HU 胡素滿 |
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SU-MAN HU 胡素滿 |
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SU-MAN HU 胡素滿 Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
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SU-MAN HU |
title |
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
title_short |
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
title_full |
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
title_fullStr |
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
title_full_unstemmed |
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry |
title_sort |
roach infestation optimization for attribute acceptance sampling plan in construction industry |
publishDate |
2013 |
url |
http://ndltd.ncl.edu.tw/handle/54yvth |
work_keys_str_mv |
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