臺灣博碩士論文加值系統

近年來環保意識的抬頭與政府法令的規定，使得逆物流漸漸成為企業界所重視的議題。透過逆物流機制，可得回收之產品經過適當的檢驗整理後重新轉換為生產的原物料，提供一般正常生產之用。如此不但可為回收品找到最大效用的處理方法，也可降低原物料採購成本、提高系統總收益。但是此種整合逆物流來源的生產程序也會影響傳統的生產系統，使得存貨管理變得複雜不易。
本研究建立考量逆物流機制之存貨管理模式。模式考量包括逆物流回收比率、回收處理時間、回收品堪用數量、回收品再製與丟棄策略、與各項回收成本等因素。這些因素將影響存貨系統中各種原物料之經濟訂購量、經濟生產批量等決策之制定。
考量存貨系統經常會受環境變化影響而需隨時調整，為能更快搜尋到最佳存貨決策，本研究利用免疫演算法中『記憶』的特性，將過去歷史最佳解資料記憶於記憶庫中。當面臨新問題（抗原）的時候，即可執行辨識程序，以迅速增生合適匹配之解（抗體），如此將可快速找到最佳解，提高系統快速反應的能力。
經由實證測試結果發現，應用免疫演算法最佳化搜尋程序，能快速制定最佳化之逆物流存貨政策，使整體供應鏈成本最低、效益最大。

Recently, reverse logistic becomes one of the important issues for all business. Through reverse logistic mechanism, the used products can be recycled from customers to manufacturer and transformed into the raw materials by certain proper inspection and process. These processes not only establish a better solution for the recovery goods, but also reduce the purchasing cost of raw materials. However, it also impacts the traditional production system such as logistic management and inventory control policy.
In this article, an inventory management system with reverse logistic was proposed, and then an inventory cost model was formed. In order to find the inventory policy quickly, we applied immune algorithms to solve these problems. Based on the memory characteristic, immune algorithms go over in solution history and distinguish the best memory in storehouse when facing a new problem. We also proposed some modifications within these processes to improve the performance.
The experimental results showed the proposed model with the immune algorithms can solve reverse logistic inventory policy in a quicker and easier manner. It also provided a more realistic model to managers.

中文摘要 I
英文摘要 II
目 次 III
圖目錄 V
表目錄 VII
第一章 緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 研究範圍與限制 2
1.4 研究流程 3
1.5 研究大綱 4
第二章 文獻探討 5
2.1 供應鏈 5
2.2 逆物流 7
2.3 逆物流存貨模式 13
2.4 逆物流總成本存貨模式 16
2.5 遺傳演算法 20
2.6 免疫演算法 24
2.7 免疫演算法之應用 28
第三章 研究方法 30
3.1 MAC模式 30
3.2 MDCF模式 37
3.3 建置免疫演算法 39
3.4 免疫演算法流程 43
第四章 模式求解與分析 48
4.1 測試程式說明 48
4.2 參數設定 53
4.3 模式求解 54
4.4 敏感度分析 60
第五章 結論 70
5.1 結論 70
5.2 未來研究方向 71
參考文獻 72

黃詩彥，企業逆物流之探索研究，東吳大學企業管理學系碩士論文，民89年。
楊昭峰，製造策略對逆向供應鏈績效之影響，國立成功大學工業管理研究所碩士論文，民91年。
管姿倫，類免疫型生物演算法的最佳結構設計，淡江大學機械與機電工程學系碩士論文，民92年。
魏凡峰，逆物流對供應鏈體系成本與時間之影響，國立成功大學工業管理研究所碩士論文，民91年。
Beamon, B. M., (1998) Supply chain design and analysis: models and methods, International Journal of Production Economics, Vol. 55, No. 3, pp. 281-294.
Brockmann, T., (1999) Warehousing trends in the 21st century, IIE Solutions, Vol. 31, No. 7, pp. 36-40.
Chakroborty, P. and T. Dwivedi, (2002) Optimal route network design for transit systems using genetic algorithms, Engineering Optimization, Vol. 34, No. 1, pp. 83-100.
Dasgupta, D. and N. A. Okine, (1997) Immunity-based systems: a survey, Proceeding of the IEEE Transactions on Systems, Man and Cybernetics, Vol. 1, pp. 369 -374.
Dasgupta, D., (1998) An overview of artificial immune systems and their applications, in: D. Dasgupta, (Ed.), Artificial Immune Systems and their Applications, Springer, first ed., pp. 3-21.
Dekker, R., E. Van der Laan, M. Salomon and A. Ridder, (1996) An (s,Q) inventory model with remanufacturing and disposal, International Journal Production Economics, Vol. 46-47, pp. 339-350.

Dowlatshahi, S., (2000) Developing a theory of reverse logistics, Interfaces, Vol. 30, No. 3, pp. 143-155.
Fleischmann, M., H. R. Krikke, R. Dekker and S. P. Flapper, (2000) A characterization of logistics networks for product recovery, Omega, Vol. 28, No. 6, pp. 653-666.
Guide, V.D.R., S. R. Jayaraman, R. Srivastava and W. C. Benton, (2000) Supply chain management for recoverable manufacturing systems, Interfaces, Vol. 30, No. 3, pp. 125-142.
Goldberg, D. E., (1989) Genetic algorithms: in search, Optimization and Machine Learning, Addison Wesley.
Hartmann, S., (2002) A self-adapting genetic algorithm for project scheduling under resource constrains, Naval Research Logistics, Vol. 49, pp. 433-448.
Harmer, P. K., P. D. Williams, H. Gunsch and B. Lamont, (2002) An artificial immune system architecture for computer security applications, IEEE Transactions On Evolutionary Computation, Vol. 6, No. 3, pp. 252-279.
Holland, J. H., (1975) Adaptation in natural and artificial system, Ann Arbor: The University of Michigan Press.
Hunt, J. E. and D. E. Cooke, (1996) Learning using an artificial immune system, Journal of Network and Computer Applications, Vol. 19, pp. 189-212.
Inderfurth, K. and E. Van der Laan, (2001) Leadtime effects and policy improvement for stochastic inventory control with remanufacturing, International Journal Production Economics, Vol. 71, pp. 381-390.
Jerne, N. K., (1973) Towards a network theory of the immune system, Annals of Immunology, Vol. 125C, pp. 373-389.
Jiao, L. and L. Wang, (2000) Novel genetic algorithm based on immunity, IEEE Proceeding of the IEEE Transactions on Systems, Man and Cybernetics, Vol. 30, No. 5, pp. 552-561.

Kiesmüller, G.. P., (2003) A new approach for controlling a hybrid stochastic manufacturing/remanufacturing system with inventories and different leadtimes, European Journal of Operational Research, Vol. 147, pp. 62-71.
Lee, Z. J., C. Y. Lee and S. F. Su, (2002) An immunity-based ant colony optimization algorithm for solving weapon-target assignment Problem, Applied Soft Computing, Vol. 2, pp. 39-47.
Minner, S., (2001) Strategic safety stocks in reverse logistics supply chains, International Journal Production Economics, Vol. 71, pp. 417-428.
Neely, A., M. Gregory and K. Platts, (1995) Performance measurement system design, International Journal of Operations and Production Management, Vol. 15, No. 4, pp. 80-116.
Richter K. and J. Weber, (2001) The reverse Wagner/Whitin model with variable manufacturing and remanufacturing cost, International Journal Production Economics, Vol. 71, pp. 447-456.
Ruud, H., E. Van der Laan and K. Inderfurth, (2000) How to set the holding cost rates in average cost inventory models with reverse logistics?, The International Journal of Management Science, Vol. 28, pp. 409-415.
Sena, G., G. Isern and D. Megherbi, (2001) Implementation of a parallel genetic algorithm on a cluster of workstations: the traveling salesman problem, a case study, Future Generation Computer Systems, Vol. 17, No. 4, pp. 477-488.
Stock, J. R., (2001) The 7 Deadly Sins of Reverse Logistics, Material Handling Management, Vol. 56, No. 3, pp. 5-12.
Taheri, S. A. and G. Calva, (2001) Imitating the human immune system capabilities for multi-agent federation formation, Proceedings of the IEEE International Symposium on Intelligent Control, pp. 25-30.
Teunter, R. and E. Van der Laan, (2002) On the non-optimality of the average cost approach for inventory models with remanufacturing, International Journal Production Economics, Vol. 79, pp. 67-73.
Thierry, M., M. Salomon, J. Van Nunen and L. Van Wassenhove, (1995) Strategic issues in product recovery management, California Management Review, Vol. 37, No. 2, pp. 11-135.
Van der Laan, E. and M. Salomon, (1997) Production planning and inventory control with remanufacturing and disposal, European Journal of Operational Research, Vol. 102, pp. 264-278.
Van der Laan, E., M. Salomon and R. Dekker, (1999) An investigation of leadtime effects in manufacturing/remanufacturing systems under simple push and pull control strategies, European Journal of Operational Research, Vol.115, pp. 195-214.
Van der Laan, E. and M. Salomon, (1997) Production planning and inventory control with remanufacturing and disposal, European Journal of Operational Research, Vol.102, pp. 264-278.
Van der Laan, E., R. Dekker and M. Salomon, (1996) Product remanufacturing and disposal: A numerical comparison of alternative control strategies, International Journal Production Economics, Vol. 45, pp. 489-498.
Van der Laan, E., (2003) An NPV and AC analysis of a stochastic inventory system with joint manufacturing and remanufacturing, International Journal Production Economics, Vol. 81-82, pp. 317-331.