A single machine learning effect scheduling problem with release times
碩士 === 逢甲大學 === 統計與精算所 === 96 === Recently learning effects in scheduling have received considerable attention in the literature. Moreover, most researchers assume that the jobs are available at all times. The learning scheduling problems with release times are then very limited. This paper investig...
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ndltd-TW-096FCU053360132015-11-27T04:04:37Z http://ndltd.ncl.edu.tw/handle/91317619738545721894 A single machine learning effect scheduling problem with release times 具有學習效果與到達時間單機排程問題之研究 Peng-Hsiang Hsu 徐鵬翔 碩士 逢甲大學 統計與精算所 96 Recently learning effects in scheduling have received considerable attention in the literature. Moreover, most researchers assume that the jobs are available at all times. The learning scheduling problems with release times are then very limited. This paper investigates a single-machine scheduling with a job-position learning model of release times where its objective is to minimize the makespan. The problem has been proven an NP-hard problem. Therefore, we will firstly apply a branch-and-bound algorithm incorporating with developing some powerful dominance properties and lower bounds for the optimal solution for the problem, and we then provide an efficient heuristic algorithm to obtain the near-optimal solution. Finally, we also conduct the computational experiments to further indicate that the branch-and-bound algorithm can solve most instances up to job size 36 within a reasonable amount of time, and the worst case of the heuristic is only with the maximum of the average error percentage of less than 0.11%. Wen-Chiung Lee Chin-Chia Wu 李文炯 吳進家 2008 學位論文 ; thesis 50 zh-TW |
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碩士 === 逢甲大學 === 統計與精算所 === 96 === Recently learning effects in scheduling have received considerable attention in the literature. Moreover, most researchers assume that the jobs are available at all times. The learning scheduling problems with release times are then very limited. This paper investigates a single-machine scheduling with a job-position learning model of release times where its objective is to minimize the makespan. The problem has been proven an NP-hard problem. Therefore, we will firstly apply a branch-and-bound algorithm incorporating with developing some powerful dominance properties and lower bounds for the optimal solution for the problem, and we then provide an efficient heuristic algorithm to obtain the near-optimal solution. Finally, we also conduct the computational experiments to further indicate that the branch-and-bound algorithm can solve most instances up to job size 36 within a reasonable amount of time, and the worst case of the heuristic is only with the maximum of the average error percentage of less than 0.11%.
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Wen-Chiung Lee |
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Wen-Chiung Lee Peng-Hsiang Hsu 徐鵬翔 |
author |
Peng-Hsiang Hsu 徐鵬翔 |
spellingShingle |
Peng-Hsiang Hsu 徐鵬翔 A single machine learning effect scheduling problem with release times |
author_sort |
Peng-Hsiang Hsu |
title |
A single machine learning effect scheduling problem with release times |
title_short |
A single machine learning effect scheduling problem with release times |
title_full |
A single machine learning effect scheduling problem with release times |
title_fullStr |
A single machine learning effect scheduling problem with release times |
title_full_unstemmed |
A single machine learning effect scheduling problem with release times |
title_sort |
single machine learning effect scheduling problem with release times |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/91317619738545721894 |
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