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研究生:楊松達
研究生(外文):Sung-Da Yung
論文名稱:迴流式多階平行機生產排程之研究
論文名稱(外文):Scheduling of reentrant flow shop with multiple processors
指導教授:黃榮華黃榮華引用關係
指導教授(外文):Rong-Hwa Huang
學位類別:碩士
校院名稱:輔仁大學
系所名稱:管理學研究所
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2007
畢業學年度:95
語文別:中文
論文頁數:46
中文關鍵詞:流程式工廠迴流式多目標蟻群最佳化平行機
外文關鍵詞:flow shopreentrantmultiple objectsant colony optimizationmultiple processors
相關次數:
  • 被引用被引用:2
  • 點閱點閱:190
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
當前的企業在面臨激烈的外在的競爭壓力下,要如何有效的配置資源,提升效率,以提升企業的競爭力是每個企業所面臨的一大挑戰,而透過生產管理中的排程技術,可以提高交期的準確性,增加產能,提升企業的競爭力。
在過去傳統排程的假設中,每個工作最多只會通過一台機器一次,而在迴流式工作站裡,一個工作可能會通過一台機器多次,我們在一些高科技業以及某些特定生產系統中都可以發現具有這種特性的生產系統,而針對這樣生產特性的研究,近年來越來越受到學者的重視。
當我們回顧有關於迴流式多階平行機生產排程的相關研究時,發現其多為只考慮單一衡量準則,在實際運作上已經不能滿足公司的需求,因此我們提出以同時考慮訂單延遲成本、工件等待的成本、以及機器閒置的成本為目標,並試圖嘗試以蟻群演算法求解這類在排程上極為複雜的問題。
本研究分別以數學規劃與蟻群演算法,以模擬資料比較Lingo 8.0與蟻群演算法之結果,證明蟻群演算法在應用於這類的問題上具有相當不錯的有效性與健全度,其時效性遠優於Lingo 8.0,可以在合理時間內提供品質不錯的求解效果。
The industrial environment is getting more and more competitive today. It is a big challenge for companies to enhance their competency by using their resources efficiently and raising the productivity. Through scheduling technology, we can deliver our products in time, increase our productivity, and enhance our competency.
In the traditional setting of scheduling, each job only process on one stage once. However, a job could pass certain stage for several times in a reentrant flow shop. And such kind of producing system can be found in some high tech industry and some specific producing systems. Production sequencing problem with reentrant work flow is getting more and more popular in recent year.
As we review all the literatures about the reentrant flow shop with multiple processors, we found that most of them only consider single object, which is not sufficient to fulfill what companies really need today. So we consider the multiple objects, the cost of tardiness, job waiting time, and machine idling time. And we try to apply the ant colony system to solve the NP-complete scheduling problem.
Our study uses the integer programming and ant colony system, and we compare the results by simulated data. We prove that the ant colony system is good at timeliness and robustness. And it’s much better than LINGO 8.0 in timeliness. It can provide a quality solution within a reasonable time.
第 壹 章 緒論 1
第 一 節 問題背景與研究動機 1
第 二 節 研究目的 4
第 三 節 研究範圍與限制 5
第 四 節 研究流程 8

第 貳 章 文獻探討 10
第 一 節 流程式工廠 10
第 二 節 迴流式生產排程 13
第 三 節 螞蟻族群最佳化演算法 14

第 參 章 研究方法 18
第 一 節 問題描述 18
第 二 節 蟻群演算法程序 22
第 三 節 釋例 24

第 肆 章 研究方法 29
第 一 節 測試資料之建立 29
第 二 節 迴流式多階平行機生產排程模型測試 31
第 三 節 大規模問題 37
第 四 節 結果分析與討論 38

第 伍 章 研究方法 39
第 一 節 結論 39
第 二 節 建議 40
參考文獻 41
中文部分
1.江朋南(2003)。蟻族系統在零工型排程問題之應用。國立台灣科技大學工業管理系碩士論文,台北市。
2.江柏彥(2006)。蟻群系統於多目標流程式排程效解之研究。私立天主教輔仁大學管理學研究所碩士論文,台北縣。
3.官長輝(2003) 。基因演算法於國道客運最適車數及排程之整合研究。私立天主教輔仁大學管理學研究所碩士論文,台北縣。
4.陳禎祥(2003)。最大完工時間極小化的迴流工廠排程之研究。台灣科技大學工業管理系博士學位論文,台北市。
英文部分
1.Adams, J., Balas, E., & Zawack, D. (1988). The shifting bottleneck procedure for job-shop scheduling. Management Science, 34, 391-401.
2.Brah, S. A. & Hunsucker, J. L. (1991). Branch and bound algorithm for the flow shop with multiple processors. European Journal of Operational Research, 51, 88-99.
3.Brah, S. A. & Loo, L. L. (1999). Heuristics for scheduling in a flow shop with multiple processors. European Journal of Operational Research, 113(1), 113-122.
4.Brah, S. A. & Wheeler, G. E. (1992, November). Comparison of local scheduling rules in a flow shop with multiple processors: A simulation. TIMS/ORSA joint national meeting, San Francisco.
5.Campbell, H. G., Dudek, R. A., & Smith, M. L. (1970). An heuristic algorithm for the n job m machine sequencing problem. Management Science, 16/B, 630-637.
6.Choiy, S. W., Kimy, Y. D., & Leez, G. C. (2005). Minimizing total tardiness of orders with reentrant lots in a hybrid flow shop. International Journal of Production Research, 43(11), 2149–2167.
7.Dannenbring, D. G. (1977). Procedures for estimating optimal solution values for large combinatorial problems. Management Science, 23(12), 1273-1283.
8.Demirkol, E. & Uzsoy, R. (2000). Decomposition methods for reentrant flow shops with sequence-dependent setup times. Journal of Scheduling, 3, 155-177.
9.Dorigo, M. (1992). Optimization, learning and natural algorithms. Unpublished doctorial dissertation, Dipartmento di Elettronica, Politecnico di Milano, IT.
10.Dorigo, M., & Di Caro, G. (1999). “The ant colony optimization meta-heuristic. ” In F. Glover (ed.). New Ideas in Optimization(11-32). London, U.K: McGraw-Hill.
11.Dorigo, M. & Gambardella, L. M. (1997). Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation, 1, 53-66.
12.Dorigo, M., Maniezzo, V., & Colorni, A. (1991). Positive feedback as a search strategy (Tech. Rep. No. 91-016). Italy: Politecnico di Milano.
13.Dorigo, M., Maniezzo, V., & Colorni, A. (1996). Ant system: Optimization by a colony of cooperating agents. IEEE Transactions on Systems, Man, and Cybernetics-Part B, 26(1), 29-41.
14.Gambardella, L. M. & Dorigo, M. (2001). An ant colony system hybridized with a new local search for the sequential ordering problem. Inform Journal on Computing, 12(3), 237-255.
15.Gangadharan, R. & Rajendran, C. (1994). A simulated annealing heuristic for scheduling in a flow shop with bicriteria. Computers and Industrial Engineering, 27 (1), 473-476.
16.Graves, S. C., Meal, H. C., Stefek, D., & Zeghmi, A. H. (1983). Scheduling of re-entrant flow shops. Journal of Operations Management, 3, 197-207.
17.Gupta, J. N. D. (1972). Heuristic algorithms for multistage flow shop scheduling problem. AIIE Transactions, 4 (1), 11-18.
18.Gupta, J. N. D. (1988). Two-stage hybrid flowshop scheduling problem. Journal of the Operational Research Society, 34(4), 359-364.
19.Gupta, J. N. D. & Tunc, E. A. (1991). Schedules for a two-stage hybrid flow shop with parallel machines at the second stage. International Journal of Production Research, 29 (7), 1489-1502.
20.Gupta, J. N. D. & Tunc, E. A. (1993). Scheduling a two-stage hybrid flow shop with separable setup and removal times. European Journal of Operational Research, 77 (3), 428-515.
21.Hark, H. & Ji, U. S. (1997). Production sequencing problem with reentrant work flows and sequence dependent setup times. Computers ind. Engng, 33, 773-776.
22.Henry, W. T. & Hunsucker, J. L. (2004). A new heuristic for minimal makespan in flow shops with multiple processors and no intermediate storage. European Journal of Operational Research, 152, 96–114.
23.Ho, J. C. (1995). Flowshop sequencing with mean flow time objective. European Journal of Operational Research, 81, 571-578.
24.Ho, J. C. & Chang, Y. L. (1991).A new heuristic for the n-job, M-machine flow-shop problem. European Journal of Operational Research, 52(2), 194-202.
25.Hundal, T. S. & Rajgopal, J. (1988). An extension of Palmer's heuristic for the flow-shop scheduling problem. International Journal of Production Research, 26 (6), 1119-1124.
26.Hunsucker, J. L. & Shah, J. R. (1992). Performance of priority rules in a due date flow shop. Omega, 20 (1), 73-89.
27.Hunsucker, J. L. & Shah, J. R. (1994). Comparative performance analysis of priority rules in a constrained flow shop with multiple processors environment. European Journal of Operational Research, 72 (1), 102-114.
28.Johnson, S. M. (1954). Optimal two- and three-stage production schedules with setup times included. Naval Research Logistics Quarterly, 1(1), 61-68.
29.Kubiak, W., Lou, S. C., & Wang, Y. M. (1990). Mean flow time minimizations in re-entrant job shops with hub. Operations Research, 44, 764-776.
30.Loukil, T., Teghem, J., & Tuyttens, D. (2005). Solving multi-objective production scheduling problems using metaheuristics. European Journal of Operational Research, 161, 42–61.
31.Nawaz, M., Enscore, E., & Ham, I. (1983). A heuristic algorithm for the m machine, n job flow shop sequence problem. OMEGA, 11 (1), 91-95.
32.Ogbu, F. A. & Smith, D. K. (1990). The application of the simulated annealing algorithm to the solution of the n/m/Cmax flow shop problem. Computers & Operations Research, 17(2), 243-253.
33.Palmer, D. S. (1965). Sequencing jobs through a multi-stage process in the minimum total time - A quick method of obtaining a near optimum. Operations Research Quarterly, 16 (1), 101-107.
34.Pearn, W. L., Chung, S. H., Chen, A. Y., & Yang, M. H. (2003). A case study on the multistage IC final testing scheduling problem with reentry. Int. J. Production Economics, 88, 257–267.
35.Rajendran, C. & Chaudhuri, D. (1990). Heuristic algorithms for continuous flow-shop problem. Naval Research Logistics, 37, 695-705.
36.Rajendran, C. & Chaudhuri, D. (1992a). A multi-stage parallel-processor flowshop problem with minimum flowtime. European Journal of Operational Research, 57, 111-122.
37.Rajendran, C. & Chaudhuri, D. (1992b). Scheduling in n-job, m-stage flow shop with parallel processors to minimize makespan. International Journal of Production Economics, 27, 137-143.
38.Santos, D. L., Hunsucker, J. L., & Deal, D. E. (1995). Global lower bounds for flow shops with multiple processors. European Journal of Operational Research, 80, 112-120.
39.Sawik, T. (2000). Mixed integer programming for scheduling flexible flow lines with limited intermediate buffers. Mathematical and Computer Modeling, 31, 39-52.
40.Stützle, T. & Hoos, H. (1997). ‘’Max-min ant system and local search for combinatorial optimization problems’’. In Voss, S., Martello, S., Osman, I. H., & Roucairol, C. (Eds.), Meta-heuristics: Advances and trends in local search paradigms for optimization. Boston, MA: Kluwer Academic Publishers.
41.Yang, B. P., Pegden, C. D., & Enscore, E. E. (1984). A survey and evaluation of static flowshop scheduling heuristics. International Journal of Production Research, 22(1), 127.
42.Zheng, W. X., Nagasawa, H., & Nishiyama, N. (1993). Single-machine scheduling for minimizing total cost with identical, asymmetrical earliness and tardiness penalties. International Journal of Production Research, 31, 1611-1620.
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