(3.230.154.160) 您好!臺灣時間:2021/05/07 23:33
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:王清育
研究生(外文):Ching-Yu Wang
論文名稱:應用啟發式演算法求解手機測試認證之最適排程
論文名稱(外文):Heuristic algorithms development for the scheduling of cellular phone testing
指導教授:蔡坤穆蔡坤穆引用關係
指導教授(外文):Kune-Muh Tsai
學位類別:碩士
校院名稱:國立高雄第一科技大學
系所名稱:運籌管理所
學門:商業及管理學門
學類:行銷與流通學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:93
中文關鍵詞:啟發式方法禁忌演算法手機測試認證非相關平行機器排程問題派工法則
外文關鍵詞:Tabu searchMobile testing certificationUnrelated machines in parallelHeuristic methodDispatching rule
相關次數:
  • 被引用被引用:0
  • 點閱點閱:190
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
本研究是針對手機測試認證的工作進行排程,由於整個手機檢測的排程類型應歸屬於非相關平行機器排程問題(Rm),且每個測試項目(Test case)所能指派的機台不盡相同,同時所需的測試時間會因機台種類不同而有所差異,因此必須找尋適當的派工法則來進行TC的指派。而本研究的研究目的為找出能讓關鍵機台使用率最高,同時能在交期日內如期完工且測試時數並非最短的最適排程,而排程出來的結果必須能為公司賺取最大的利潤。因此本研究根據手機產業的特性,選擇SPT、LPT、LFM-LFJ三種法則來進行指派,然後再進一步利用禁忌搜尋法找尋最適的排程,最後研究結果顯示,禁忌搜尋法能比派工法則所產生的啟發式方法充分使用交期內的產能,且有效提升關鍵機台的使用率,同時待測設備(EUT)的數量也會影響到整體產能的運用。
This study developed a program which is responsible for the process scheduling of the mobile testing certification. We considered the mobile testing as unrelated machines in parallel (Rm) while each test case (TC) is dispatched in different machines. Since the testing time of each machine is varied, it is critical to find the proper dispatching rule for TC dispatching. This study would like to find a dispatching mode, which based on the trade-off between producing the highest utilization rate in the critical machine, finishing the project in due date, and getting the highest profit.
To investigate the optimized scheduling, we considered the characteristics of the mobile industry while dispatching rule of SPT, LPT, LFM-LFJ, and the Tabu search are adopted. Findings presented that Tabu search may improve more the utilization rate of the critical machine than the heuristic method. Furthermore, the number of Equipment under test (EUT) may affect the integral productivity of machine.
1.封面
2.書面頁
3.論文口試委員會審定書
4.中文摘要
5.英文摘要
6.致謝
7.目錄
8.表目錄
9.圖目錄
10.論文本文
11.參考文獻
12.附錄
13.書背
1. 中文文獻
王立志(2003)。供應鏈實戰手冊。鼎誠資訊。
周清江與黃信強(2002)。運用基因演算法於平行機器之工作排程。資訊管理展望,4(1),47-59。
張玉鈍與曾毓文(2002)。運用系統模擬與遺傳演算法從事非相關平行機器排程之研究。台北科技大學學報,35(1),303-320。
2. 英文文獻
Allahverdi, A., Ng, C. T., Cheng, T. C. E., & Kovalyov, M. Y. (2008). A survey of scheduling problems with setup times or costs. European Journal of Operational Research, 187, 985-1032.
Aytug, H., Bhattacharyya, S., Koehler, G. J., & Snowdon, J. L. (1994). A review of machine learning in scheduling. IEEE transactions on engineering management, 41(2), 165-171.
Calhoun, K. M., Deckro, R. F., Moore, J. T., Chrissis, J. W., & Hove, J. C. V. (2002). Planning and re-planning in project and production scheduling. Omega, 30, 155-170.
Chen, C. L., & Chen, C. L. (in press). A bottleneck-based heuristic for minimizing makespan in a flexible flow line with unrelated parallel machines. Computers & Operations Research.
Chen, W. J. (2007). Minimizing total flow time and maximum tardiness with periodic maintenance. Journal of Quality in Maintenance Engineering, 13(3), 293-303.
Cho, S. (2005). A distributed time-driven simulation method for enabling real-time manufacturing shop floor control Computers & Industrial Engineering 49(4), 572-590.
Gao, L., Wang, C., Wang, D., Yin, Z., & Wang, S. (1998). A production scheduling system for parallel machines in an electrical appliance plant. Computers & Industrial Engineering, 35(1-2), 105-108.
Glover F. (1990). Tabu search. ORSA Journal on Computing.
Gupta, J. N. D., Neppalli, V. R., & Werner, F. (2001). Minimizing total flow time in a two-machine flowshop problem with minimum makespan. Int. J. Production Economics, 69, 323-338.
Herrmann, J., Proth, J. M., & Sauer, N. (1997). Heuristics for unrelated machine scheduling with precedence constraints. European Jourmal of Operational Research, 102, 528-538.
Jeong, B., Kim, S., & Lee, Y. (1999). An assembly schedular for TFT LCD manufacturing. Paper presented at the Proceedings of The 4th Annual International Conference on Industrial Engineering Theory, Applications and Practice, San Antonio, Texax, USA.
Kurz, M. E., & Askin, R. G. (2003). Comparing scheduling rules for flexible flow lines. Int. J. Production Economics, 85, 371-388.
Lee, H. C., & Dagli, C. H. (1997). A parallel genetic-neuro scheduler for job-shop scheduling problems. Int. J. Production Economics, 51, 115-122.
Lee, K. K. (2008). Fuzzy rule generation for adaptive scheduling in a dynamic manufacturing environment. Applied Soft Computing, 8, 1295-1304.

Logendran, R., McDonell, B., & Smucker, B. (2007). Scheduling unrelated parallel machines with sequence-dependent setups. Computers & Operations Research, 34, 3420-3438.
Mok, P. Y., Kwong, C. K., & Wong, W. K. (2007). Optimisation of fault-tolerant fabric-cutting schedules using genetic algorithms and fuzzy set theory. European Jourmal of Operational Research, 177, 1876-1893.
Pinedo, M. (2002). Scheduling: Theory, Algorithms, and Systems (2 ed.). Upper Saddle River, N.J.: Prentice Hall.
Rocha, P. L., Ravetti, M. G., Mateus, G. R., & Pardalos, P. M. (2008). Exact algorithms for a scheduling problem with unrelated parallel machines and sequence and machine-dependent setup times. Computers & Operations Research, 35, 1250-1264.
Silva, C., & Magalhaes, J. M. (2006). Heuristic lot size scheduling on unrelated parallel machines with applications in the textile industry. Computers & Industrial Engineering, 50, 76-89.
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔