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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Main Authors: SU-MAN HU, 胡素滿
Other Authors: Yong-Huang Lin
Format: Others
Language:zh-TW
Published: 2013
Online Access:http://ndltd.ncl.edu.tw/handle/54yvth
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spelling 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
collection NDLTD
language zh-TW
format Others
sources NDLTD
description 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.
author2 Yong-Huang Lin
author_facet Yong-Huang Lin
SU-MAN HU
胡素滿
author SU-MAN HU
胡素滿
spellingShingle SU-MAN HU
胡素滿
Roach Infestation Optimization for Attribute Acceptance Sampling Plan in Construction Industry
author_sort 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
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