本研究探討都市內連鎖型商店的車輛途程問題，建構出一套仿照管理者思考模式的路線分割方法，模擬管理者採納過去經驗、傾向由既有模式修改，且不因部分訂單需求改變而重頭規劃的排程習慣。利用免疫演算法中「記憶」的特性，建置路線資料庫，儲存歷史最佳的規劃模式，當面臨的需求相同時直接由資料庫提取歷史資料，而遭遇新問題時，則由資料庫中提取相近的規劃模式進行演化，並且將改變的規模與各車輛工作負荷的平衡納入成本函式，反應對第一線員工造成的影響。本研究以Java程式語言撰寫演算法，便於相容於一般之計算機。以貼近實際規劃思維的方式協助高雄市7-Eleven物流業者規劃每日例行的配送，減輕人員負擔，並藉由演算法的記憶性協助企業經驗傳承。本研究模擬隨機分配的需求，規劃高雄市310家7-Eleven的配送路線，並藉修改工作時間與服務時間等參數，為企業在車輛固定成本與人員變動成本間進行取捨，計算出最適合的車輛派遣數量。

This study constructs a partition model which imitates the thinking method of planners, adopt their past experience, and make minor modification to the existing plan without complete re-scheduling. The "memory" properties of an immune algorithm are used to build a database. If the same problem is encountered, the system will directly retrieve the historical data from the database. If a new problem is encountered, the system will extract a similar regional pattern from the database to evolve into a new optimal partition mode. The contribution of this study is to demonstrate a model which mimics planners’ thinking in their actual planning under urban traffic restrictions to improve the efficiency of daily urban logistics, and transmit the planning experience via "memory" characteristics. This study uses random delivery requirement to simulate everyday planning of 310 7-Eleven stores in Kaohsiung City. And exam the outcome after changing the work hours or services time to help enterprise choose the best decision of asset purchasing by taking trade-off between personnel overtime costs and fixed costs of vehicle purchase.

一、 中文參考文獻
1. 中田信哉 (2002) 物流‧配送。大地出版社。
二、 英文參考文獻
1. Bodin, L., Golden, B., Assad, A., & Bull, D. (1983). Routing and scheduling of vehicles and crews: The state of the art. Computers and Operation Research, 10, 63–111.
2. Bland, R. G., & Shallcross, D. F. (1989). Large travelling salesman problems arising from experiments in X-ray crystallography: A preliminary report on computation. Operations Research Letters, 8(3), 125-128.
3. Bersini, H. (1991). Immune network and adaptive control. In: F.J. Varela and P. Bourgine, Editors, Proceedings of the First European Conference on Artificial Life, MIT Press, 217–226.
4. Busacker, F., & Saaty, T. (1966). Finite Graphs and Their Applications. New York, McGraw-Hill.
5. Carter, J. H. (2000). The Immune System as a Model for Pattern Recognition and Classification. Journal of the American Medical Informatics Association, 7(1), 28-41.
6. Carvalho, D. R., & Freitas, A. A. (1991). An immunological algorithm for discovering small-disjunct rules in data mining. In: Specter et al. (Eds.), Proceedings of the 1991 Genetic and Evolutionary Computation Conference, 401–404.
7. Castro, L. N., & Timmis, J. (2002). Artificial Immune Systems: A New Computational Intelligence Approach, Springer-Verlag.
8. Chung, J. S., Jung, H. K., & Hahn, S.Y. (1998). A study on comparison of optimization performances between immune algorithm and other algorithms, IEEE transactions on magnetics, 34(5), 2972–297.
9. Clarke, G., & Wright, J. W. (1964). Scheduling of Vehicles from a Central Depot to a Number of Delivery Points. Operations Research, 12(4), 568-581.
10. Coello Coello, C. A., & Cruz Cortés, N., (2002). An approach to solve multiobjective optimization problems based on an artificial immune system, in: First International Conference on Artificial Immune Systems (ICARIS), J. Timmis and P. J. Bentley (eds.), University of Kent at Canterbury Printing Unit: Canterbury, UK, 212-221.
11. Cohn JL. (1978). Multi-objective programming and planning, Academic Press, New York.
12. Cui, X., Li, M., & Fang, T. (2001). Study of population diversity of multi-objective evolutionary algorithm based on immune and entropy principles. In: Proceedings of the 2001 Congress on Evolutionary
13. Dasgupta, D. (1999). Artificial Immune Systems and their Application, Springer, Berlin, (Education series).
14. Dasgupta, D., & Gonzalez, F. (2002). An immunity-based technique to characterize intrusions in computer security networks, IEEE Transactions on Evolutionary Computation, 6(3), 281–291.
15. Dreissig, W., & Uebach, W. (1990). Personal communication.
16. Duckstein, L. (1984). Multiobjective optimization in structural design: the model choice problem, In: New directions in structural optimization, ed. E Atrek, et al., John Wiley and Sons Ltd.
17. Eschenauer, H., Koski, J., & Osyczky, A. (1990). Multi-criterion design optimization: procedures and applications, Springer, New York.
18. Garey, M. R., & Johnson, D. S. (1979). Computers and Intractability: A Guide to the Theory of NP-completeness, Freeman, San Francisco, CA..
19. Grötschel, M., Jünger, M., & Reinelt, G. (1991). Optimal control of plotting and drilling machines: A case study. Mathematical Methods of Operations Research, 35(1), 61-84.
20. Hajela, P., & Lee, J. (1996). Constrained genetic search via schema adaptation: An immune network solution. Structural and Multidisciplinary Optimization, 12(1), 11-15.
21. Harmer, P. K., Williams, P. D., Gunsch, G. H.,&. Lamont, G. B. (2002). An artificial immune system architecture for computer security applications, IEEE Transactions on Evolutionary Computation, 6(3) , 252–280.
22. Hart, E., & Timmis, J. (2005). Application Areas of AIS: The Past, The Present and The Future (pp.483-497).
23. Hollander, S. C., & Omura, G. S. (1989). Chain store developments and their political, strategic, and social interdependencies, Journal of Retailing, 65(3), 299-325.
24. Hu, Z., Ding, Y., & Shao, Q. (2009). Immune co-evolutionary algorithm based partition balancing optimization for tobacco distribution system. Expert Systems with Applications, 36(3, Part 1), 5248-5255.
25. Hu, Z.-H. (2010). A multiobjective immune algorithm based on a multiple-affinity model. European Journal of Operational Research, 202(1), 60-72.
26. Hunt, J. E., & Cooke, D. E. (1996), Learning using an artificial immune system, Journal of Network and Computer Applications 19, 189–212.
27. Jünger, M., & Reinelt, G. (1995) "The traveling salesman problem." In M. Ball, T. Magnanti, C. L. Monma & G. Nemhauser (Eds.), Handbook on Operations Research and Management Sciences: Networks. North-Holland, Amsterdam.
28. Karp, R. M. (2010). Reducibility Among Combinatorial Problems (pp. 219-241).
29. Kim, D. H., & Lee, H. (2004), Intelligent control of nonlinear power plant using immune algorithm based multi-objective optimization. In: Proceedings of the 2004 IEEE International Conference on Networking, Sensing and Control, 1388–1393
30. Kohler, U. (1997). An innovating concept for city logistics. Paper presented at the The 4th World Congress on Intelligent Tranport Systems (ITS), Berlin, German.
31. Koski, J. (1984). Multicriterion optimization in structural design, In: New directions in structural optimization, ed. E Atrek, et al., (eds), John Wiley and Sons Ltd.
32. Lawler, E. L. (1985). The Traveling Salesman Problem: A Guided Tour of Combinatorial Optimization: Wiley.
33. Laporte, G. (1992). The vehicle routing problem: An overview of exact and approximate algorithms. European Journal of Operational Research, 59(3), 345-358.
34. Lau, H. Y. K., & Wong, V. W. K. (2007). An immunity approach to strategic behavioral control. Engineering Applications of Artificial Intelligence, 20(3), 289-306.
35. Lenstra, J. K., & Kan, A. H. G. R. (1975). Some Simple Applications of the Travelling Salesman Problem. Operational Research Quarterly (1970-1977), 26(4), 717-733.
36. Li, G., Zhou, R.-G., Duan, L., & Chen, W.-F. (1999). Multiobjective and multilevel optimization for steel frames. Engineering Structures, 21(6), 519-529.
37. Liao, G.-C. (2006). Short-term thermal generation scheduling using improved immune algorithm. Electric Power Systems Research, 76(5), 360-373.
38. Mester, D., Bräysy, O., & Dullaert, W. (2007). A multi-parametric evolution strategies algorithm for vehicle routing problems. Expert Systems with Applications, 32(2), 508-517.
39. Mori, M., Tsukiyama, M., & Fukada, T. (1998). Adaptive scheduling system inspired by immune system. In: Proceedings of the 1998 IEEE Systems, Man and Cybernetics Conference, 1614–1619.
40. Ore, O. (1996). Graphs and Their Uses. The Mathematical Association of America.
41. Ratliff, H. D., & Arnon, S. R. (1983). Order-Picking in a Rectangular Warehouse: A Solvable Case of the Traveling Salesman Problem. Operations Research, 31(3), 507-521.
42. Reinelt, G. (1994). The Traveling Salesman: Computational Solutions for TSP Applications: Springer Verlag.
43. Ringuest, J. L. (1992). Multiobjective optimization: behavioral and computational considerations, Kluwer Academic, Norwell, MA.
44. Ruske, W. (1994). City logistics - solutions for urban commercial transport by cooperative operation management. Paper presented at the OECD Seminar on Advanced Road Transport Technologies, Omiya, Japan.
45. Solomon, M. (1983). Vehicle routing and scheduling with time window constraints: Models and algorithms. Technical report, College of Business Admin., Northeastern University, 83-42.
46. Taniguchi, E., & Thompson, R. (2002). Modeling City Logistics. Transportation Research Record: Journal of the Transportation Research Board, 1790(1), 45-51.
47. Taniguchi, E., Thompson, R. G., Yamada, T., & van Duin, R. (2001). City Logistics: Network Modelling and Intelligent Transport Systems: Pergamon.
48. Tarakanov, A. O., & Tarakanov, Y. A. (2005). A comparison of immune and genetic algorithms for two real-life tasks of pattern recognition, International Journal of Unconventional Computing, 1(4), 357–374.
49. Timmis, J. & Knight, T. (2001). Artificial immune systems: Using the immune system as inspiration for data mining. In: Abbass, H. A. et al., Data Mining, 209–230.
50. Timmis, J., Edmonds, C., & Kelsey, J.(2004). Assessing the performance of two immune inspired algorithms and a hybrid genetic algorithm for function optimisation, IEEE Proceedings of the Congress on Evolutionary Computation, 1,1044–1051.
51. Wang, H. S. (2008). Expert Interview. Tainan, Taiwan.
52. Wilson, R. J. (1986). Introduction to graph theory. New York, John Wiley & Sons, Inc.
53. Yoo, J., & Hajela, P. (1999). Immune network simulations in multicriterion design. Structural and Multidisciplinary Optimization, 18(2), 85-94.
三、 網站資料
1. 統一超商官方網站，(http://www.7-11.com.tw/)
2. 捷盟行銷股份有限公司官方網站，(http://www.supei.com.tw/about/company.htm)
3. 交通部全球資訊網，(http://www.motc.gov.tw/)