臺灣博碩士論文加值系統

物流中心因具有集中處理、專業分工、降低庫存、掌握通路以及減少資金積壓等優點，近年來企業紛紛投入物流中心的建置，也因此物流中心的管理成為一重要課題。在實務上，物流中心主要之價值活動可分為進貨、儲存、撿貨、以及出貨四項。而在過去許多的研究中明確的指出撿貨作業為物流中心內成本最高的活動，因此許多文獻探討如何針對撿貨效率提升。
物流中心因貨品及訂單的不同而採取不同的撿貨作業系統；本研究所探討之撿貨作業系統專門處理物流中心內之散裝訂單，散裝訂單為訂購量較小因而不需整箱訂購之貨品，撿貨員撿取後將貨品置入物流箱內並透過輸送帶將物流箱送至下一撿貨區。在實務上本研究之撿貨作業系統會採取訂單分割之策略，也就是將貨品分散於數條撿貨線以增加處理速度，而由於貨品分散於數條撿貨線，在各撿貨線撿貨完畢之後必需將同一筆訂單分散於各撿貨線之物流箱上匯整起來。實務上透過緩衝區來儲存處理完畢之物流箱以等待其他撿貨線上同一筆訂單之物流箱到齊之後匯整成一筆完整之訂單，而由於緩衝區長度的限制，一旦緩衝區的空間不足以存放物流箱，則連帶的會使該段緩衝區上游之撿貨線停工，而造成最大完工時程的增加。本研究舉例說明訂單處理順序對最大完工時程的影響，並透過訂單處理順序最小化撿貨作業之最大完工時程(Cmax)。
由於實務上訂單筆數數量龐大，因此其解集合空間相當龐大，若考慮現實上時效性之問題，傳統之作業研究方式求得最佳解往往曠日廢時，無法提供即時之訂單排序，因此本研究採用基因演算法作為求解之工具並以C語言實作該演算法。
研究結果顯示，在不同的實驗因子組合下本研究所提之模型現況改善率為2%至10%。而當訂單筆數越多、撿貨線數目增加越多、緩衝區越短的情況下，本研究對現況解的改進越高。

Because of the benefits of lowering the inventory level and controlling the distribution channels, many enterprises have devoted to build their self-own distribution centers. And therefore the management and control of the operation in distribution centers (DCs) becomes an important issue. In practice, the main activities in DCs are receipt, storage, order picking and dispatch, and according to the previous literatures, order picking accounts for most of the total operating cost and thus many literatures focused on order picking to enhance the efficiency in DCs.
DCs adopt several kinds of order picking system. The order picking system in this study is mainly to handle the bulk-broken items. In this system all items are picked into containers and containers would be sent by conveyor belt to the next picking zone. In practice the order picking may adopt order split strategy to boost the order picking speed, and because of the adoption of these picking strategies the container of an specific order is separated on different order picking lines hence those separated containers should be accumulated together to form a complete order. In order to accumulate those goods of the same order, there should be a buffer in the tail of the order picking lines to store these goods. And the length of buffer is limited and once the buffer is all used, the order picking line which the buffer belongs to should be stopped to wait the buffer release and the order picking efficiency is reduced. This study shows how the sequence of order picking affects the order picking time (Cmax), and the purpose of this study is to find a order picking sequence to minimize the times of buffer jam and to minimize Cmax .
In practice the there are hundreds of orders and the search space is extremely large, so it is hard to apply the traditional operation research method to find the optimum solution because of the time limit. In this research the genetic algorithm is applied and is implemented with the C language.
The computational results show the improvement to the status quo in different situations is from 2% to 10%. The more the number of orders, the more the number of order picking lines and the shorter the length of buffer, the more the improving rate.

目錄 I
圖目錄 II
表目錄 III
第壹章 緒論 1
第一節 研究背景 1
第二節 研究動機 4
第三節 研究目的 5
第四節 研究流程 6
第貳章 文獻探討 8
第一節 撿貨作業 8
第二節 撿貨系統 10
第三節 撿貨作業改善之基本原則 12
第四節 相關文獻彙整 15
第參章 研究方法 21
第一節 本研究撿貨作業之環境 22
第二節 研究問題描述 24
第三節 模式建構 29
第四節 基因演算法 31
第肆章 實證結果 40
第一節 本研究之基因演算法設計 40
第二節 實驗設計與測試問題 44
第三節 計算結果範例 50
第四節 計算結果與討論 53
第伍章 結論與建議 60
第一節 結論 60
第二節 建議 63
參考文獻 64
附錄 論文程式碼 70

中文部分
1. 李勝隆，基因演算法於印刷電路板鑽孔排程之應用，元智大學工業工程與管理碩士論文，民國91年。
2. 物流中心揀貨作業，經濟部商業自動化系列叢書，台北：經濟部商業司，民國84年。
3. 物流經營管理實務，經濟部商業司，民國85年。
4. 葉昭憲，「改善基因演算法之文獻回顧」，台灣水利，第44 卷，第一期，頁92-105，民國85年。
5. 董福慶、陳明德，物流中心揀貨作業，經濟部商業自動化系列叢書，民國84年。
6. 錢文俊，空服員之雇用及排班整合研究，輔仁大學管理學研究所碩士論文，民國92年。
7. 官長輝，基因演算法於國道客運最適車數及排程之整合研究，輔仁大學管理學研究所碩士論文，民國92年。
英文部分
1. Ackerman, K. B., Practical Handbook of Warehousing, Van Nostrand Reinhold , New York, NY, (1990).
2. Armstrong, R. D., W. D., Cook and A. L. Saipe, , "Optimal Batching in a semi-automated order picking system," Journal of the operational research society, Vol. 30, No. 8, pp. 711-720, (1979).
3. Chaime M.E., "Operations sequencing in automated warehousing systems", I.J.P.R., Vol. 30, No. 10, pp. 2401-2409, (1992).
4. Coyle, J.J., Bardi, The Management of Business Logistics, (1986).
5. Davis L., "Job-shop scheduling with genetic algorithms," Proceedings of the First International Conference on Genetic Algorithms and their Applications, Hillsdale: Lawrence Erlbaum. pp. 136-140, (1985).
6. Djerid L, M-C and Portmann, "How to keep good schemata using crossover operators for the permutation problems," International Transactions in Operations Research, Vol. 7, No. 6, pp.637-651, (2000).
7. Elsayed, E. A. and R. G. Stern, "Comtuterized algorithms for order processing in automated warehousing systems," International Journal of Production Research, Vol.21, No.4, pp.579 — 586, (1983).
8. Elsayed, E. A., "Algorithms for optimal material handling in automatic warehousing systems," International Journal of Production Research, Vol.19, No.5, pp.525-535, (1981).
9. Elsayed, E. A., and O. I. Unal, "Order batching algorithms and travel-time estimation for automated storage/retrieval systems," International Journal of Production Research, Vol. 27, No. 7, pp. 1097-1114, (1989).
10. Eshelman, L. J., Caruanu, R.A. and J.D. Schaffer, Biases in crossover landscape. In Proc. 3rd International Conference Genetic Algorithms, 10-19, (1989).
11. Fox BR, McMahon MB. In: Rawlins GJE, editor. Genetic operations for sequencing problems, foundations of genetic algorithms. San Mateo: Morgan Kaufmann Publishers; pp. 284-300, (1991).
12. Francis, R. L. and J. A. White, "Facility Layout and Location - An Analytical Approach", Prentice-Hall, Englewood Cliffs, NJ, (1974).
13. Frazelle, E.H. and J.M. Apple, Warehouse Operations in The Distribution Management Handbook, Tompkins, J.A. and Harmelink, D.A., McGraw-Hill, New York, NY, (1994).
14. Frazelle, E.H., and G.P. Sharp, "Correlated assignment strategy can improve order-picking operation," Industrial Engineering Vol. 21, No. 4, pp. 33-37, (1989).
15. Frazelle, E. H., S.T. Hackman, U. Passy, and L.K., Platzman, The forward-reserve problem, Optimization in Industry 2, Ciriani. T.A. and Leachman, R.C., John Wiley, pp.43-61. (1994).
16. Gibson, D. R., and G. P. Sharp, "Order batching procedures," European Journal of Operational Research, vol. 58, no. 1, pp. 57-67, (1992).
17. Goetschalckx, M. and H.D. Ratliff, "An efficient algorithm to cluster order picking items in a wide aisle," Engineering Costs and Production Economics, vol. 13, pp. 263-271, (1988)
18. Goldberg DE, GAs in search, Optimization and Machine learning. Reading, MA: Addison-Wesley, (1989).
19. Grefenstette, J., "Optimization of Control Parameters for Genetic Algorithms," IEEE Transactions on Systems, Man, and Cybernetics SMC vol. 16, no.1 , pp. 122-128. (1986).
20. Ishibuchi H., N. Yamamoto, T. Murata, and H, Tanaka, "Genetic Algorithms and Neighbourhood Search Algorithms for Fuzzy Flowshop Scheduling Problems", Fuzzy Sets and systems, vol. 67, no. 1, pp. 81-100, (1994).
21. Hackman, S.T. and M.J. Rosenblatt, "Allocating items to an automated storage and retrieval system, " IIE Transactions, vol.22 no.1, pp. 7-14, (1990).
22. Hall, R. W., "Distance approximations for routing manual pickers in a warehouse," IIE Transactions. vol. 25, no. 4, pp. 76-87, (1993).
23. Hausman, W. H., L. B. Schwarz, and S. C. Graves, "Optimal storage assignment in automatic warehousing systems," Management Science, vol. 22, no. 6, pp. 629-638, (1976).
24. Holland JH. Adaption in natural and artifcial systems. Ann Arbor: The University of Michigan Press, (1975).
25. Hwang, H., W. Bake, and M. K. Lee, "Clustering algorithms for order picking in an automated storage and retrieval systems," International Journal of Production Research, vol. 26, no. 2, pp. 189-201, (1988).
26. Jarvis Jay M. and Edward D. McDowell, "Optimal Product Layout in an Order Picking Warehouse," IIE Transactions, vol. 23, no. 1, pp. 93-102, (1991).
27. Jeroen P. van den Berg, J. P., "A literature survey on planning and control of warehousing systems," IIE Transactions, vol. 31, no. 8, pp. 751-762, (1999).
28. Jog P et al. The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem. Proceedings of the Third IGCA, San Mateo, pp. 110-115, (1989).
29. M. Srinivas and L. M. Patnaik, Genetic Algorithms: A Survey, IEEE Computer, June, (1994).
30. Mitchell, M., "An Introduction to Genetic Algorithms", Massachusetts Institute of Technology, pp. 170-171, (1996).
31. Petersen II, C.G. & R. W. Schmenner, "An evaluation of routing and volume-based storage policies in an order picking operation," Decision Sciences, vol. 30, no. 2, pp. 481-501, (1999).
32. Petersen II, C.G., "The impact of routing and storage policies on warehouse efficiency," International Journal of Operations & Production Management, vol. 19, no. 10, pp. 1053-1064, (1999).
33. Petersen II, C.G., "An evaluation of order picking policies for mail order companies," Production and Operations Management, Vol. 9, No. 4, pp. 319-335,(2000).
34. Petersen, C. G., "An evaluation of order picking routing policies", International Journal of Operations & Production Management, vol. 17, no. 11, pp.1098-1111, (1997).
35. Petersen, Chales, "An evaluation of order picking routing policies," International Journal of Operations & Production, Vol. 17, Iss. 11, pg.1098, (1997).
36. Portmann MC, Vignier A Performance study on crossover operators keeping goos schemata for some scheduling problems, preprint, (2002).
37. Rosenblatt, M. J., and A. Eynan, "Deriving the optimal boundaries for class-based automatic storage/retrieval systems", Management Science, vol. 35, no. 12, pp. 1519-1524 (1989).
38. Rosenwein, M. B., "A comparison of heuristics for the problem of batching orders for warehouse selection," International Journal of Production Research, vol. 34, no. 6, pp. 657-664, (1996).
39. Rosenwein, M.B., “An application of cluster analysis to the problem of locating items within a warehouse,” IIE Transactions, vol. 26, no. 1, pp. 101-103, (1994)
40. Srikanth K. Iyera, and Barkha Saxenab, “Improved genetic algorithm for the permutation flowshop scheduling problem,” Computers & Operations Research vol. 31 pp. 593-606, (2004).
41. Starkweather T et al. “A comparison of genetic sequencing operators,” Proceedings of Fourth IGCA, pp. 69-76, (1991).
42. Ulder NLJ. Genetic local search algorithms for the traveling salesman problem. In: Schwefel HP, Manner R, editors, (1990).
43. Van den Berg, J.P., G.P. Sharp Gademann, A.J.R.M. and Pochet Y., “Forward-reserve allocation in a warehouse with unit-load replenishments,” European Journal of Operational Research, vol. 111, no. 1, pp. 98-113, (1998).
44. Van Oudheusden, D.L. and Zhu, W., “Storage layout of AS/RS racks based on recurrent orders,” European Journal of Operational Research, vol. 58 no. 1, pp. 48-56, (1992).