博碩士論文 963202072 詳細資訊




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姓名 張恭文(Kung-Wen Chung)  查詢紙本館藏   畢業系所 土木工程學系
論文名稱 隨機旅行時間下拌合廠臨時性故障之混凝土生產與拌合車派遣規劃之研究
(Ready Mixed Concrete Production and Truck Dispatching Planning When RMC Mixer Is Breakdown Unexpectedly under Stochastic Travel Times)
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摘要(中) 目前預拌混凝土的生產已進入自動化與電腦化的時期,但在混凝土生產作業安排與拌合車運送排程上,實務界仍以人工經驗的方式進行規劃。此方式缺乏系統最佳化分析,往往會造成資源的浪費,降低營運績效。雖然Yan and Lai (2007)與Yan et al. (2008)曾針對正常日與考量加班日等二種作業下之確定性預拌混凝土拌合廠生產排班與拌合車排程規劃問題,利用數學規劃方法,以最小營運成本目標,並考量相關營運限制下,分別構建一整合預拌混凝土生產排班和拌合車排程模式。然而,現實的營運上充滿了頗多的臨時或隨機事件以擾動原規劃的排程,例如在即時的營運中,當預拌混凝土廠遭遇臨時性的故障時,則預拌廠的生產作業受影響,連帶著拌合車的運送排程亦將受影響;又如在實際的營運中,各拌合廠至各工地間之旅行時間常為隨機值(可能成某種分佈),並非為一固定值,其值將影響拌合車的運送排程規劃與績效。因此本研究以系統最佳化的觀點,針對隨機旅行時間下拌合廠臨時性故障之混凝土生產與拌合車派遣規劃問題發展適合之模式及求解演算法,以提供決策者輔助工具,有效地規劃拌合廠的生產排班與拌合車的運送排程。
本研究利用時空網路流動技巧以定式拌合車在時空中的流動狀況及預拌廠在時間中的生產情況,並根據問題特性加入適當的額外限制,以滿足實務的營運條件,並據以構建模式。本模式可定式為含額外限制之整數網路流動問題,屬NP-hard問題,在面對實務大型的問題時,難以在有限的時間內求得最佳解。因此,為有效地求解實務大型問題,本研究利用問題分解策略,並配合使用數學規劃套裝軟體CPLEX,發展一有效的求解演算法。最後,為評估本模式與演算法之實際求解績效,本研究以台灣一拌合廠之實際營運資料為範例進行測試與分析,結果甚佳,顯示本研究所發展之模式與求解演算法可為實務業者之參考,以有效地處理隨機旅行時間下混凝土生產與拌合車排程擾動問題。
摘要(英) The production of ready mixed concrete (RMC) has been automatic and computerized, but the RMC production scheduling and truck dispatching are still manually determined with staff experience. Consequently, the resulting solution, though feasible, could possibly be inferior. Yan and Lai (2007) and Yan et al. (2008) have respectively developed a deterministic model that combines RMC production scheduling and truck dispatching in the same framework, for general and overtime conditions. However, in actual operations many stochastic incidents may occur to disturb the original plan. For example, if an RMC plant is broken down, then both the RMC production scheduling and truck dispatching would be affected. Moreover, the travel time between an RMC plant and a construction site is usually stochastic (particularly with a certain distribution) in practice, which could affect the RMC production scheduling and truck dispatching. Therefore, in this research we focus on the RMC production and truck schedule adjustment problem under stochastic travel time when an RMC mixer is broken down unexpectedly to develop a suitable model from the system optimization perspective. The model is expected to be useful planning tool for carriers to decide on their optimal RMC production scheduling and truck dispatching in their operations.
We employ time-space network flow techniques to formulate the RMC truck flows and the RMC production in the dimension of time and space, coupled with suitable side constaints comply real operating requirements, to develop the model. The model is formulated as an integer network flow problem with side constraints, which is characterized as NP-hard and is difficult be be optimally solved in a reasonable time for large-scale problems. In order to efficiently solve large-scale problems occurring in real world, we develop a solution algorithm. To evaluate the model and solution algorithms, we perform a case s`tudy using real operating data from a Taiwan RMC firm. The test results show that the model and the solution algorithm are good and could be useful references for carriers to handle RMC productin and truck schedule perturbations under stochastic travel times.
關鍵字(中) ★ 預拌混凝土
★ 生產排班
★ 拌合車排程
★ 臨時事件
★ 隨機擾動
★ 時空網路
★ 含額外限制網路流動問題
關鍵字(英) ★ network flow problem with side constraints
★ time-space network
★ ready mixed concrete
★ production scheduling
★ truck dispatching
★ incident
★ stochastic disturbance
論文目次 摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VII
表目錄 VIII
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的與範圍 2
1.3 研究方法與程式架構 3
第二章 文獻回顧 5
2.1現況分析 5
2.2預拌混凝土生產作業與拌合車調派問題 7
2.3工廠生產排程問題 9
2.4時窗限制之車輛派遣/排程問題 11
2.5時空網路之相關文獻 13
2.6隨機擾動之相關理論與文獻 15
2.6.1 隨機性問題相關理論 15
2.6.2 隨機擾動相關文獻 17
2.7 大型含額外限制之整數網路流動問題啟發式演算法 20
2.8 小結 23
第三章 模式構建 25
3.1 問題描述 25
3.2 隨機性之即時拌合廠作業模式 25
3.2.1 模式條件設定 26
3.2.1.1 基本假設 26
3.2.1.2 給定資訊 28
3.2.2 時空網路 29
3.2.3 限制說明 36
3.2.4 非預期性懲罰成本( )設計 41
3.2.5 模式符號說明 44
3.2.6 數學定式 49
3.3 確定性之即時拌合廠作業模式 53
3.3.1 確定性模式之時空網路 53
3.3.2 符號說明 55
3.3.3 數學定式 55
3.4 模擬評估方法 57
3.5 小結 58
第四章 模式求解 59
4.1 啟發解法架構 59
4.2 單一車輛定線法 62
4.3 目標值下限解 62
4.3 小結 63
第五章 範例測試 64
5.1資料輸入 64
5.1.1澆置作業資料 64
5.1.2營運成本資料 65
5.2 模式發展 65
5.2.1 問題規模 65
5.2.2 模式輸入資料 67
5.3 電腦演算環境及設定 67
5.3.1 電腦演算環境 67
5.3.2 相關程式設定 68
5.3.3 模式輸出資料 68
5.4 測試結果與分析 69
5.4.1隨機狀況數目 70
5.4.2隨機性之即時拌合廠作業排程模式結果 71
5.4.3 模式比較分析 73
5.5 敏感度分析 75
5.5.1 拌合車規模敏感度分析 75
5.5.2 需求大小敏感度分析 77
5.5.3 隨機分配模式敏感度分析 79
5.5.3.1 平均數變動 79
5.5.3.2 標準差變動 81
5.5.4 違反冷縫限制懲罰成本( ) 82
5.5.5 達冷縫機率上限(100%)之時間感度分析 84
5.6情境分析 86
5.6.1拌合廠故障修復所需時間之情境分析 86
5.6.2開始規劃時間之情境分析 88
5.6.3問題規模大小之情境分析 90
5.6.4非預期性懲罰成本之冷縫機率分配型態情境分析 92
5.7小結 94
第六章 結論與建議 95
6.1 結論 95
6.2 建議 96
6.3 貢獻 97
參考文獻 99
附 錄 108
附錄一 CPLEX Callable Library Code 108
附錄二 旅行時間分布圖 109
附錄三 隨機狀況模擬數目測試結果 110
附錄四 即時拌合廠作業班次 111
附錄五 拌合車規模敏感度分析 113
附錄六 隨機分配模式敏感度分析 114
附錄七 違反冷縫限制懲罰成本敏感度分析結果 115
附錄八 拌合廠及工地之營運時間 116
參考文獻 1. 申生元,「多趟次車輛途程與排程問題」,行政院國家科學委員會,NSC90-2218-E155-010 (2002)。
2. 江朋南,「蟻群系統在零工式排程問題之應用」,碩士論文,台灣科技大學工業管理研究所(2003)。
3. 余秀梅,「多元商品模式應用在動態貨櫃調度問題之研究」,碩士論文,國立成功大學交通管理科學研究所(1994)。
4. 吳宗憲,「結合模擬技術與專家系統應用於公車之排班作業」,碩士論文,國立台灣大學土木工程學系(1994)。
5. 林恩仕,「以派遣中心為基礎之預拌混凝土廠派車模式」,碩士論文,成功大學土木工程研究所(2003)。
6. 侯育周,「隨機性班機到離延誤下動態機門指派之研究」,碩士論文,國立中央大學土木工程學系(2007)。
7. 江孝頤,「隨機旅行時間下混凝土生產作業及拌合車的調派決策之研究」,碩士論文,國立中央大學土木工程學系(2008)。
8. 曹智翔,「短期需求擾動下動態醫療物資輸配送之研究」,碩士論文,國立中央大學土木工程學系(2007)。
9. 陳俊豪,「因應臨時事件變動租用數機場共用櫃檯即時指派之研究」,碩士論文,國立中央大學土木工程學系(2005)。
10. 陳毓卿,「因應臨時事件航機停機修護排程調整最佳化之研究」,碩士論文,國立中央大學土木工程學系(2007)。
11. 游俊雄、丁國樑,「需求反應旅次運載模擬模式應用於捷運營運班表之評估」,運輸計劃季刊,第二十七卷,第三期,頁489-508(1998)。
12. 楊大輝、李綺容,「需求變動下之航空貨運網路規劃」,運輸學刊,第十九卷,第二期,頁169-189 (2007)。
13. 廖建韋,「醫療物資訂購及配送排程規劃之研究」,碩士論文,國立中央大學土木工程學系(2007)。
14. 趙宏逵,「市區預拌混凝土廠商生產排程車輛調派與路線問題之研究」,碩士論文,國立交通大學交通運輸研究所(1986)。
15. 劉方旗,「市區公車排班與即時機動調度之研究--以新竹客運為例」,碩士論文,國立交通大學運輸科技與管理學系(1998)。
16. 顏上堯、何淑萍,「飛航排程暨班次表之建立」,運輸計劃季刊,第二十三卷,第一期,73-90頁(1994)。
17. 顏上堯、杜宇平、陳怡妃,「因應臨時事件機場共用櫃檯即時指派之研究」,運輸計劃季刊,第三十三卷,第一期,頁59- 81(2004)。
18. 顏上堯、齊志仁、湯慶輝,「隨機需求下多目標長途客運排程模式之研究」,運輸計畫季刊,第三十四卷,第一期,頁93-118(2005)。
19. 顏上堯、羅智騰,「因應預期性航具維修之系統性飛航排程」,中國土木水利工程學刊,第八卷,第三期,頁447-456(1996)。
20. 羅敏綺,「隨機需求下捷運系統營運模擬模式之構建-以台北市木柵線為例」,碩士論文,國立成功大學交通管理科學系(1998)。
21. Abara, J., “Applying integer linear programming to the fleet assignment problem,” Interfaces, 19, pp.20-28(1989).
22. Agin, N. and Cullen, D., “An algorithm for transportation routing and vehicle loading,” in Geisler, M. (Ed.), Logistics, pp.1-20, North Holland, Amsterdam (1975).
23. Akkan, C. and Karabat, S., “The two-machine flowshop total completion time problem: Improved lower bounds and a branch-and-bound algorithm,” European Journal of Operational Research, 159, pp.420-429(2004).
24. Arroyo, J.E.C. and Armentano, V.A., “Genetic local search for multi-objective flowshop scheduling problems,” European Journal of Operational Research, 167(3), pp.717-738(2005).
25. Azia, N., Gendreaua, M. and Potvin, J.Y., “An exact algorithm for a single-vehicle routing problem with time windows and multiple routes,”European Journal of Operational Research, 178(3), pp.755-766(2007).
26. Barnhart, C., Johnson, E.L., Nemhauser, G.L., Savelsbergh, M. W.P. and Vance, P.H., “Branch-and-price: column generation for solving huge integer programs,” Operations Research, 46, pp. 316-329(1998).
27. Benders, J.F., “Partitioning procedures for solving mixed-variables programming problems,” Numerische Mathematik, 4, pp. 238-252(1962).
28. Bent, R. W. and Hentenryck, P. V., “Scenario-based planning for partially dynamic vehicle routing with stochastic customers,” Operations Research, pp.52, 977-987(2003).
29. Camerini, P.K., Fratta, L. and Maffioli, F., “On improving relaxation methods by modified gradient techniques,” Mathematical Programming Study, 3, pp. 6-25(1975).
30. Chang, Y.L., “Time window capacity analysis for synchronous production,” Proceedings of the Second International Conference on Automation Technology, 1, Taipei, pp.17-26(1992).
31. Chen, C.Y. and Kornhauser, A.L., “Decomposition of convex mulitcommodity network flow problem,” Report SOR-90-19, Dept. of Civil Engineering and Operations Research, Princeton University, Princeton, NJ(1990).
32. Chen, C. H., S. Yan and C. H. Tseng (2009), “Inter-city Bus Scheduling for Allied Carriers,” Transportmetrica. (accepted)
33. Cheng, T.M. and Feng, C.W., “An effective simulation mechanism for construction operations,” Automation in Construction, 12, pp.227-244(2003).
34. Clarke, L. W., Hane, C. A., Johnson, E. L. and Nemhauser, G. L., “Maintenance and crew considerations in fleet assignment,” Transportation Science, 30, pp.249-260(1996).
35. Desaulniers, G., Desrosiers, J., Dumas, Y., Solomon, M.M. and Soumis, F., “Daily aircraft routing and scheduling,” Management Science, 43, pp.841-855(1997).
36. Diana, M. and Dessouky, M.M., “A new regret insertion heuristic for solving large-scale dial-a-ride problems with time windows,” Transportation Research Part B, 38, pp.539–557(2004).
37. Equi, L., Gallo, G., Marziale, S. and Weintraub, A., “A combined transportation and scheduling problem,” European Journal of Operational Research, 97(1), pp.94-104(1997).
38. Feng, C.W. and Wu, H.T., “Integrating fmGA and CYCLONE to optimize the schedule of dispatching RMC trucks,” Automation in Construction, 15 (2) pp.186-199(2006).
39. Feng, C.W. and Wu, H.T., “Using genetic algorithms to optimize the dispatching schedule of RMC cars,” Proceedings of the 17th International Symposium on Automation and Robotics in Construction, Taipei, pp.927-932(2000).
40. Feng, C.W., Cheng, T.M. and Wu, H.T., “Optimizing the schedule of dispatching RMC trucks through genetic algorithms,” Automation in Construction, 13, pp.327-340(2004).
41. Fisher, M. L., “The Lagrangian relaxation method for solving integer programming problem,” Management Science, 27, pp. 1-18(1981).
42. Glover, F. and M. Laguna, Tabu search, Kluwer Academic Publishers, Norwell, MA (1997).
43. Hane, C. A., Barnhart, C., Johnson, E. L., Marsten, R., Nemhauser, G. L. and Sigismondi, G., “The fleet assignment problem: solving a large-scale integer program,” Mathematical Programming Study, 70, pp.211-232(1995).
44. Healy, P., “A tool for adjusting the flight schedule during high volume iregular operations,” Proceedings of the AGIFORS 32nd Annul Symposium, pp.53-64(1992).
45. Hsu, C.I., Hung, S.F. and Li, H.C., “Vehicle routing problem with time-windows for perishable food delivery,” Journal of Food Engineering 80, pp.465–475(2007).
46. Hurink, J. and Knust, S., “Flow-shop problems with transportation times and a single robot,” Osnabrucker Schriften zur Mathematik, Reihe P, Nr. 201(1998).
47. Husbands, P., “Genetic algorithms for scheduling,” AISB Quarterly, 89(1994).
48. Ibaraki, T., Kubo, M., Masuda, T., Uno, T. and Yagiura, M., “Effective local search algorithms for the vehicle routing problem with general time windows constraint,” Transportaion Science, 39, pp.106-232(2005).
49. Jarrah, A.I., Yu, G., Krishnamurthy, N. and Rakshit, A.,”A decision support framework for airline flight cancellations and delays,” Transportation Science, 27(3), pp.266-280(1993).
50. Kennington, J. L. and Shalby, M., “An effective subgradient procedure for minimum cost multicommodity flow problem,” Management Science, 23, pp.994-1004(1977).
51. Kenyon, A.S. and Morton, D.P., “Stochastic vehicle routing with random travel times,” Transportation Science, 37 (1), pp.69-82(2003).
52. Lamatsch, A., “An approach to vehicle scheduling with depot capacity constraints,” in Desrochers, M. and Rousseau, J. M.(eds.), Computer Aided Transit Scheduling, Lecture Notes in Economics and Mathematical System 386, Springer Verlag, Berlin, Heidelberg, pp. 181-195(1992).
53. Lee, B.C., “Routing problem with service choices, flight transportation laboratory,” Report R86-4, Massachusetts Institute of Technology, MA (1986).
54. Lee, C.Y. and Chen, Z.L., “Machine scheduling with transportation considerations,” Working Paper, #98-08, Department of Systems Engineering, University of Pennsylvania (1998).
55. Levin, A., “Scheduling and fleet routing models for transportation systems,” Transportation Science, 5, pp. 232-255(1971).
56. Levin, A., “Some fleet routing and scheduling problems for air transportation systems,” Flight Transportation Laboratory Report R68-5, Massachusetts Institute of Technology, MA (1969).
57. List, G.F., Wood, B., Nozick, L.K., Turnquist, M.A., Jones, D.A., Kjeldgaard, E.A. and Lawton, C.R., “Robust optimization for fleet planning under uncertainty,” Transportation Research, part E, 39, pp.209-227(2003).
58. Lu, M., Anson, M., Tang, S.L. and Ying, Y.C., “HKCONSIM: A practical simulation solution to planning concrete plant operations in Hong Kong,” Journal of Construction Engineering and Management, 129(5), pp.547-554(2003).
59. Luh, P. B., Zhao, X., Wang, Y. and Thakur, L.S., “Lagrangian relaxation neural network for job shop scheduling,” Proc. of International Conference on Robotics and Automation, Leuven, Belgium, pp.1799-1804(1998).
60. Matsatsinis, N.F., “Towards a decision support system for the ready concrete distribution system: A case of a Greek company,” European Journal of Operational Research, 152 (2), pp. 487-499(2004).
61. Mesquita, M. and Paixao, J., “Multiple depot vehicle scheduling problem: a new heuristic based on quasi-assignment algorithm,” in Desrochers, M. and Rousseau, J. M.(eds.), Computer Aided Transit Scheduling, Lecture Notes in Economics and Mathematical System 386, Springer Verlag, Berlin, Heidelberg, pp. 181-195(1992).
62. Mulvery, J.M. and Ruszczynski, A., “A New scenario decomposition method for large-scale stochastic optimization,” Operations Research, 43(3), pp.477-490(1995).
63. Mulvery, J.M., Vanderbei, R.J. and Zenios, S.A., “Robust optimization of large-scale systems,” Operations Research, 43(2), pp.254-281(1995).
64. Naso, D., Surico, M., Turchiano, B. and Kaymak, U., “Genetic algorithms in supply chain scheduling of ready mixed concrete,” ERIM report series research in management, ERS-2004-096-LIS, Erasmus Research Institute of Management (2004).
65. Powell, W.B. and Ioannis, A.K., “Shipment routing algorithms with tree constraints,” Transportation Science, 26, pp. 230-245(1992).
66. Rego, C. and Roucairol, C., “Using tabu search for solving a dynamic multi-terminal truck dispatching problem,”European Journal of Operational Research, 83(2), pp.411- 429(1995).
67. Shmoys, D.B., Stein, C. and Wein, J., “Improved approximation algorithms for shop scheduling problems,” SIAM Journal on Computing, 23(3), pp.617-632(1994).
68. Simpson, R. W., “A review of scheduling and routing model for airline scheduling,” IX AGIFORS Symposium, Broadway, England(1969).
69. Solomon, M. M., Vehicle routing and scheduling with time windows constraints: models and algorithms. Ph.D. dissertation, Department of Decision Science, University of Pennsylvania, USA (1983).
70. Stancu-Minasian, I.M., “Stochastic programming with multiple objective functions,” Editura Academiei, Bucharest(1984).
71. Subramanian, R., Scheff, R. P., Quillinan, J. D., Wiper, D. S. and Marsten, R. E., “Coldstart: fleet assignment at Delta Air Lines,” Interface, 24(1), pp.104-120(1994).
72. Teodorovic, D. and Guberinic, S., “Optimal dispatching strategy on an airline network after a schedule perturbation,” European Journal of Operational Research, 15, pp. 178-182(1984).
73. Teodorovic, D., Airline operations research, Gordon and Breach Science Publishers, New York (1988).
74. Thengvall, B. G., Bard, J. F. and Yu, G., “Balancing user preferences for aircraft schedule recovery during airline irregular operations,” IIE Transactions on Operations Engineering, 32(3), pp.181-193(2000).
75. Thengvall, B.G., Yu, G. and Bard, J. F., “Multiple fleet aircraft schedule recovery following hub closure,” Transportation Research, Part A, 35(4), pp.289-308(2001).
76. Varadharajan, T. K. and Rajendran, C., “A multi-objective simulated-annealing algorithm for scheduling in flowshops to minimize the makespan and total flowtime of jobs,” European Journal of Operational Research, 167, pp.772-795(2005).
77. Wang, D. Z. W. and Lo, H. K., “Multi-fleet ferry service network design with passenger preferences for differential services,” Transportation Research Part B, 42, pp.798-822(2008).
78. Wang, L. and Zheng, D. Z., “An effective optimization strategy for job shop scheduling problems,” Computers and Operations Research, 28, pp.585-596(2001).
79. Wang, L. and Zheng, D.Z., “A modified genetic algorithm for job shop scheduling,” International Journal of Advanced Manufacturing Technology, 20, pp.72-76(2002).
80. Yamada, T. and Nakano, R., “Job shop scheduling by simulated annealing combined with deterministic local search,” Metaheuristics International Conference, Hilton, Breckenridge, Colorado, USA, pp.344-349(1995).
81. Yan, S. and Chen, C.H., “Coordinated flight scheduling models for allied airlines,” Transportation Research, Part C, 15(4), pp.246-264(2007).
82. Yan, S., Chen, C.H. and Chen, C.K., “Long-term manpower supply planning for air cargo terminals,” Journal of Air Transport Management, 12 (4), pp.175-181(2006a).
83. Yan, S. and Lai, W.S., “An optimal scheduling model for ready mixed concrete supply with overtime considerations,” Automation in Construction, 16, pp.734-744(2007).
84. Yan, S., Lai, W.S. and Chen, M.N., “Production scheduling and truck dispatching of ready mixed concrete,” Transportation Research, Part E, 44, pp.164-179(2008a).
85. Yan, S. and Lin, C.G., “Airline scheduling for the temporary closure of airports,” Transportation Science, 31(1), pp.72-82(1997).
86. Yan, S., Shieh, C. W. and Chen, M., "A simulation framework for evaluating airport gate assignments,” Transportation Research, part A, 36(10), pp.885-898(2002).
87. Yan, S. and Shih, Y.L. “A time-space network model for work team scheduling after a major disaster,” Journal of the Chinese Institute of Engineers, 30 (1), pp.63-55(2007).
88. Yan, S. and Tang, C.H., “A heuristic approach for airport gate assignments for stochastic flight delays,” European Journal of Operational Research, 180 (2), pp. 547-567(2007).
89. Yan, S., Tang, C.H. and Fu, T.C., “An airline scheduling model and solution algorithms under stochastic demands,” European Journal of Operational Research, Vol. 190, pp. 22-39(2008b).
90. Yan, S., Tang, C.H. and Shieh, C.N., “A simulation framework for evaluating airline temporary schedule adjustments following incidents,” Transportation Planning and Technology, 28(3), pp.189-211(2005).
91. Yan, S. and Yang, D.H., “A decision support framework for handling schedule perturbation,” Transportation Research, Part B, 30(6), pp.405-419(1996).
92. Yan, S. and Young, H.F., “A decision support framework for multi-fleet routing and multi-stop flight scheduling,” Transportation Research, Part A, 30(5), pp.379-398(1996).
93. Yan, S., Chen C. Y. and Lin S. C., “Ship Scheduling and Container Transshipment Planning for Liners in Short Term Operations,” submitted to Journal of Marine Science and Technology, Springer. (accepted)
94. Zayed, T. M. and Halpin, D.W., “Simulation of concrete batch plant production,” Journal of Construction Engineering and Management, 127(2), pp.132-141(2001).
95. Zayed, T. M. and Minkarah, I., “Resource allocation for concrete batch plant operation: Case study,” Journal of Construction Engineering and Management, 130 (4), pp.560-569(2004).
96. Zhu, K., Tan, K.C. and Lee, L.H., “Heuristic methods for vehicle routing problem with time windows,” Artificial Intelligence in Engineering,15(3), pp. 281-295(2000).
指導教授 顏上堯(Shang-Yao Yan) 審核日期 2009-7-21
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