請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64551完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 楊烽正(Feng-Cheng Yang) | |
| dc.contributor.author | Yu-Nien Chen | en |
| dc.contributor.author | 陳昱年 | zh_TW |
| dc.date.accessioned | 2021-06-16T17:54:04Z | - |
| dc.date.available | 2014-08-20 | |
| dc.date.copyright | 2012-08-20 | |
| dc.date.issued | 2012 | |
| dc.date.submitted | 2012-08-12 | |
| dc.identifier.citation | Chin Soon, C., Malcolm Yoke Hean, L., Appa Iyer, S. & Kheng Leng, G., 2006. A bee colony optimization algorithm to job shop scheduling. Simulation Conference, WSC 06. Proceedings of the Winter, 1954-1961.
Colorni, A., Dorigo, M., Maniezzo, V. & Trubian, M., 1994. Ant system for job-shop scheduling. Belgian Journal of Operations Research, Statistics and Computer Science, 34 (1), 39-53. Davis, L., 1985. Job shop scheduling with genetic algorithms. Proceedings of the 1st International Conference on Genetic Algorithms. L. Erlbaum Associates Inc., 136-140. Dell'amico, M. & Trubian, M., 1993. Applying tabu search to the job-shop scheduling problem. Annals of Operations Research, 41 (3), 231-252. Dorigo, M., 1992. Optimization, learning and natural algorithms. Ph. D. Thesis, Politecnico di Milano, Italy. Dorigo, M. & Gambardella, L.M., 1997. Ant colony system: A cooperative learning approach to the traveling salesman problem. Evolutionary Computation, IEEE Transactions on, 1 (1), 53-66. Glover, F., 1986. Future paths for integer programming and links to artificial intelligence. Computers & Operations Research, 13 (5), 533-549. Holland, J.H., 1975. Adaptation in natural and artificial systems: An introductory analysis with applications to biology, control, and artificial intelligence: University of Michigan Press. Jain, A.S., 1998. A multi-level hybrid framework for the deterministic job-shop scheduling problem: University of Dundee. Lageweg, B.J., Lenstra, J.K., Lawler, E.L. & Kan, A.H.G.R., 1982. Computer-aided complexity classification of combinational problems. Commun. ACM, 25 (11), 817-822. Muth, J.F. & Thompson, G.L., 1963. Industrial scheduling: Prentice-Hall. Puris, A., Bello, R., Trujillo, Y., Nowe, A. & Martínez, Y., 2007. Two-stage aco to solve the job shop scheduling problem. In Rueda, L., Mery, D. & Kittler, J.: Springer Berlin / Heidelberg, 447-456. Sha, D.Y. & Hsu, C.Y., 2006. A hybrid particle swarm optimization for job shop scheduling problem. Computers & Industrial Engineering, 51 (4), 791-808. Matsuo, H., Suh C. J. & SullivanI R. S., 1988. A controlled search simulated annealing method for the general job shop scheduling problem. Working paper 03-04-88, Graduate School of Business, University of Texas, Austin. Stützle, T. & Hoos, H., 1997. Max-min ant system and local search for the traveling salesman problem. Evolutionary Computation, IEEE International Conference on, 309-314. Yang, F.C. & Chou, Y.C., 2009. Superior/inferior segment-discriminated ant system for combinatorial optimization problems. Computers & Industrial Engineering, 57 (2), 475-495. Yang, F.C. & Wang, Y.P., 2007. Water flow-like algorithm for object grouping problems. Journal of the Chinese Institute of Industrial Engineers, 24 (6), 475-488. 江朋南 (2003)，蟻族系統在零工型排程問題之應用，碩士論文，國立臺灣科技大學工業管理系。 李仁富 (2011)，仿頻寬限制資料傳輸之離散優化演算法，碩士論文，國立臺灣大學工業工程學研究所。 林典翰 (2004)，優加劣減螞蟻擇段系統應用於組合問題，碩士論文，國立臺灣大學工業工程學研究所。 潘嘉琪 (2008)，求解一般性排序優化問題的仿水流優化演算法，碩士論文，國立臺灣大學工業工程學研究所。 | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/64551 | - |
| dc.description.abstract | 本研究承襲一創新的萬用啟發式演算法「仿頻寬限制資料傳輸優化演算法」(Bandwidth Restricted Transmission-Simulated Optimization Algorithm, BRT-S) ，提出「仿頻寬限制資料傳輸之離散優化演算法應用於零工式生產排程問題」(Bandwidth Restricted Transmission-Simulated Discrete Optimization Algorithm for Job Shop Scheduling Problem, BRT-S4JSP)。BRT-S模仿網際網路資料傳輸的特性，模擬訊息傳輸者傳輸訊息。訊息傳輸者在頻寬資源有限狀況下，逐步選擇傳輸線段，建構一條完整的傳輸路徑。BRT-S模擬自然環境的劣化，使傳輸線段在演化過程中老化損毀，並執行頻寬添加及扣減作業。在BRT-S的演算規劃下，規劃符合零工式生產排程問題(Job Shop Scheduling Problems, JSP)的演算流程。研究內容針對物件排序優化問題中的零工式生產排程問題建立BRT-S4JSP求解模式，開發BRT-S4JSP求解系統求解OR-library中的JSP標竿問題，並和其他萬用啟發式演算法比較求解結果。在求解JSP標竿問題中，BRT-S4JSP能在諸多問題中求得最佳解，且求得最小完工天數時的平均目標函數評估次數較其他萬用啟發式演算法少。BRT-S4JSP在相同的停止條件下求得品質比其他萬用啟發式演算法來的佳，也在目標函數評估次數花費上較為精簡，證明本研究所提出的BRT-S4JSP法是一個適合求解零工式生產排程問題的演算法。 | zh_TW |
| dc.description.abstract | This research presents a meta-heuristic algorithm called “Bandwidth Restricted Transmission-Simulated Discrete Optimization Algorithm for Job Shop Scheduling Problem” (BRT-S4JSP) for solving Job Shop Scheduling Problem (JSP). BRT-S imitates the behavior of data transmission in the network and simulates messengers transmit messages. Messengers select the communication links and constructive a complete route under the restriction of resources. BRT-S simulates that links are subject to operations of natural deterioration and enhancement/deduction/modulation. Based on the original BRT-S computational flow, BRT-S4JSP conducts the computational flow of JSP. BRT-S is designed for solving discrete optimization problems. We develop BRTSOS4JSP solving system for Job Shop Scheduling Problem through programming language. By using the benchmark of JSP from OR-library, we compare results with other meta-heuristic algorithm then verify the feasibility of BRT-S4JSP. In the example for JSP, BRT-S can obtain optimal solutions and use less objective function evolution than others. BRT-S4JSP can obtain better solutions under the same stop criteria. This research proves BRT-S4JSP is a good meta-heuristic algorithm for Job Shop Scheduling Problems. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T17:54:04Z (GMT). No. of bitstreams: 1 ntu-101-R99546032-1.pdf: 1148925 bytes, checksum: 40fb053023c4296e12d47cca3f468b91 (MD5) Previous issue date: 2012 | en |
| dc.description.tableofcontents | 謝誌 i
摘要 ii Abstract iii 目錄 iv 圖目錄 v 表目錄 vi 第 1 章 緒論 1 1.1 研究背景 1 1.2 研究目的 2 1.3 研究流程 3 1.4 章節概要 5 第 2 章 文獻回顧 6 2.1 萬用啟發式演算法 6 2.1.1 遺傳演算法 6 2.1.2 仿水流優化演算法 8 2.1.3 蟻拓尋優法 9 2.1.4 仿頻寬限制資料傳輸優化演算法 11 2.2 零工式生產排程問題 12 第 3 章 仿頻寬限制資料傳輸之離散優化演算法應用於零工式生產排程問題 16 3.1零工式生產排程問題描述 16 3.2仿頻寬限制資料傳輸之離散優化演算法應用於零工式生產排程問題的演算流程 17 3.3小結 35 第 4 章 仿頻寬限制資料傳輸優化演算法求解系統及範例驗證 36 4.1仿頻寬限制資料傳輸優化演算法求解系統 36 4.2範例測試與比較 41 4.3小結 54 第 5 章 結論與未來研究建議 55 5.1結論 55 5.2未來研究建議 56 參考文獻 57 附錄一 零工式生產排程問題標竿問題 60 | |
| dc.language.iso | zh-TW | |
| dc.subject | 零工式生產排程問題 | zh_TW |
| dc.subject | 仿頻寬限制資料傳輸優化演算法 | zh_TW |
| dc.subject | 萬用啟發式演算法 | zh_TW |
| dc.subject | 排程 | zh_TW |
| dc.subject | Meta-heuristic Algorithm | en |
| dc.subject | Job Shop Scheduling problems | en |
| dc.subject | Scheduling | en |
| dc.subject | Bandwidth Restricted Transmission-Simulated Optimization Algorithm | en |
| dc.title | 仿頻寬限制資料傳輸之離散優化演算法應用於零工式生產排程問題 | zh_TW |
| dc.title | Bandwidth Restricted Transmission-Simulated Discrete Optimization Algorithm for Job Shop Scheduling Problems | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 100-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 歐陽超(Chao Ou-Yang),洪一薰(I-Hsuan Hong) | |
| dc.subject.keyword | 萬用啟發式演算法,零工式生產排程問題,排程,仿頻寬限制資料傳輸優化演算法, | zh_TW |
| dc.subject.keyword | Meta-heuristic Algorithm,Job Shop Scheduling problems,Scheduling,Bandwidth Restricted Transmission-Simulated Optimization Algorithm, | en |
| dc.relation.page | 84 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2012-08-13 | |
| dc.contributor.author-college | 工學院 | zh_TW |
| dc.contributor.author-dept | 工業工程學研究所 | zh_TW |
| 顯示於系所單位： | 工業工程學研究所 | |
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