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研究生:張韶銘
研究生(外文):Shao-Ming Chang
論文名稱:供應商評選模式建置—考量運輸時窗限制與供應商風險不確定性
論文名稱(外文):Supplier Selection Model Construction—Time Windows of Transportation and Uncertainty of Supplier Risk
指導教授:王河星王河星引用關係
口試委員:江梓安車振華
口試日期:2012-06-21
學位類別:碩士
校院名稱:國立臺北科技大學
系所名稱:工業工程與管理系碩士班
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:中文
論文頁數:77
中文關鍵詞:供應商評選組裝次序規劃生產線平衡問題時窗限制穩健最佳化
外文關鍵詞:Supplier SelectionAssembly Sequence PlanningSimple Assembly Line Balancing ProblemTime Window ConstraintsRobust Optimization
相關次數:
  • 被引用被引用:1
  • 點閱點閱:180
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建立供應鏈的核心競爭力是企業非常重視的議題,其中供應商評選則扮演著關鍵角色,合適的供應商將明顯地降低生產之成本與提升顧客服務水準。因此本文研究一個考量組裝次序規劃、生產線平衡與供應商風險之不確定性的供應商評選問題,並在評選準則中的運輸時間加入時窗限制,強調組裝中心如期生產的重要性,避免顧客的交貨日期延遲。為解決此供應商評選問題,本研究發展出一個穩健最佳化模式,來處理在多階供應鏈中具有供應商風險不確定性之供應商評選問題。此外,本研究也提出一種整合型基因演算法來求解穩健最佳化模式,為了驗證其求解之績效,本研究提出之演算法與另外兩個已知且目前較佳的演算法作案例實證有效性之比較。最後,提出穩健代價作分析,藉此可以探討保護程度與穩健代價之間的關係。另外,將穩健最佳化模式與確定性評選模式之結果作探究,提供決策者決定是否執行穩健規劃之必要性。

Establishing central competitiveness of supply chain is an issue strongly emphasized by enterprises. Among them, the supplier selection plays a key role. The suitable supplier will noticeably the reduce cost of production and promote Level of customer service. Therefore, this thesis studies the supplier selection problem with considering the assembly sequence planning, assembly line balancing problem, uncertainty of supplier risk, and also at transportation time of evaluation criterion to join time window constraints. The importance emphasized to assemble center to produce as scheduled, besides avoid delaying the customer''s date of delivery. This research develops a robust optimization mode, in order to solve the uncertainty of supplier risk of supplier selection problem in multi-stage supply chains. In addition, this text also puts forth the integration genetic algorithm to solve robust optimization mode. For identifying it solves of performance, these researches proposed of the algorithm have been already known with other two and better algorithm does the comparison of case substantial evidence usefulness currently. In the end, put forth the robust price analyzes. With this the study protective level and robust price both of relation. Besides, the result of robust optimization mode and determinism mode compares an investigation. Provide if the decision maker decision carries out the necessity of robust plan.

目 錄

摘 要 i
ABSTRACT ii
誌 謝 iv
目 錄 v
表目錄 vii
圖目錄 viii
第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 3
1.3 研究流程 4
第二章 文獻探討 7
2.1 供應商評選 7
2.2 組裝次序規劃 8
2.3 生產線平衡問題 10
2.4 時窗限制 12
2.5 多目標基因演算法 13
2.6 蟻群最佳化 15
2.7 穩健最佳化 16
2.7.1 Robust Optimization 17
2.7.2 Robust Counterpart Optimization 18
第三章 研究方法 20
3.1 問題描述與研究假設 20
3.2 研究架構 21
3.3 多目標最佳化數學模式 24
3.3.1 數學符號定義 24
3.3.2 多目標基本模式 26
3.3.3 穩健最佳化模式 31
3.4 整合式多目標演算法 33
3.4.1 蟻群系統動態非支配解基因演算法流程 34
第四章 實證案例與結果分析 47
4.1 案例描述 47
4.1.1 案例問題描述 47
4.1.2 實驗設計 53
4.1.3 案例結果 55
4.2 整合式多目標演算法績效評估 58
4.3 穩健規劃探討 62
第五章 結論與建議 66
參考文獻 68

表目錄

表2.1 穩健最佳化模式整理 19
表3.1 數學符號說明 24
表3.2 穩健數學符號說明 32
表4.1 頭戴式耳機之零件資訊表 48
表4.2 頭戴式耳機之結合關係資訊表 49
表4.3 頭戴式耳機之結合時間表 51
表4.4 頭戴式耳機之結合成本表 51
表4.5 各零件供應商資料表 52
表4.6 各參數組合NNS平均表 54
表4.7 各參數組合NPS平均表 54
表4.8 各參數組合ER平均表 55
表4.9 頭戴式耳機之最佳組裝次序規劃 55
表4.10 柏拉圖最佳解集合 56
表4.11 應商評選與零件採購結果 57
表4.12 各演算法執行績效之結果表 59
表4.13 保護程度Γ對目標函數的影響 62
表4.14 保護程度對穩健代價的影響 64

圖目錄

圖1.1 決策支援系統輔助示意圖 3
圖1.2 研究流程圖 6
圖2.1 組裝關聯圖 9
圖3.1 研究架構圖 23
圖3.2 蟻群系統動態非支配解基因演算法程序圖 35
圖3.3 染色體編碼示意圖 38
圖3.4 非支配解等級排序圖 39
圖3.5 排擠距離示意圖 40
圖3.6 排擠距離對分佈性的影響 41
圖3.7 輪盤法示意圖 43
圖3.8 供應商評選單點交配示意圖 43
圖3.9 生產線平衡單點交配示意圖 44
圖3.10 供應商評選雙點突變示意圖 44
圖3.11 生產線平衡雙點突變示意圖 45
圖3.12 菁英保留策略示意圖 45
圖4.1 頭戴式耳機之零件爆炸圖 48
圖4.2 頭戴式耳機之結合優先關係圖 49
圖4.3 頭戴式耳機之結合優先關係矩陣 50
圖4.4 最佳解之生產線平衡圖 57
圖4.5 各演算法之各目標比較分佈圖 61
圖4.6 保護程度對變異係數趨勢圖 64
圖4.7 保護程度對穩健代價趨勢圖 65


參考文獻

[1]A. Ben-Tal and A. Nemirovski, “Robust solutions of uncertain linear programs,” Operations Research Letters, Vol. 25, No. 1, 1999, pp. 1-13.
[2]A. Ghobadian, A. Stainer and T. Kiss, “A computerized vendor rating system,” Proceedings of the 1st International Symposium on Logistics, Nottingham, UK, 1993, pp. 321-328.
[3]A. L. Soyster, “Convex programming with set-inclusiveconstraints and applications to inexact linearprogramming,” Operations Research, Vol. 21, No. 5, 1973, pp. 1154-1157.
[4]A. R. Rahimi-Vahed, S. M. Mirghorbani and M. Rabbani, “A new particle swarm algorithm for a multi-objective mixed-model assembly line sequencing problem,” Soft Computing - A Fusion of Foundations, Methodologies and Applications, Vol. 11, No. 10, 2007, pp. 997-1012.
[5]A. Scholl, Balancing and Sequencing of Assembly Lines, 2nd Edition, Heideberg:Physica, 1996.
[6]A.N. Haq and G. Kannan, “Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model,” International Journal of Advanced Manufacturing Technology, Vol. 29, No. 7-8, 2006, pp. 826-835.
[7]B. Luo, J. Zheng, J. Xie and J. Wu, “Dynamic Crowding Distance - A new diversity maintenance strategy for MOEAS,” 4th international conference on natural computation, Vol. 1, 2008, pp. 580-585.
[8]B. Yu and Z. Z. Yang, “An ant colony optimization model: The period vehicle routing problem with time windows,” Transportation Research Part E: Logistics and Transportation Review, Vol. 47, No. 2, 2011, pp.166-181.
[9]C. A. Weber, J. R. Current and W. C. Benton, “Vendor selection criteria and methods,” European Journal of Operational Research, Vol. 50, No. 1, 1991, pp. 2-18.
[10]C. M. Fonseca and P. J. Fleming, “Genetic algorithms for multiobjective optimization: Formulation, discussion and generalization,” Proceedings of the Fifth International Conference on Genetic Algorithms, Ed. San Mateo, CA: Morgan Kauffman, 1993, pp. 416-423
[11]C. Mascle and H. Ping Zhao, “Integrating environmental consciousness in product/process development based on life-cycle thinking,” International Journal of Production Economics, Vol. 112, No. 1, 2008 , pp. 5-17.
[12]C. Zeng, T. Gu, Y. Zhong and G. Cai, “A multi-agent evolutionary algorithm for connector-based assembly sequence planning,” Procedia Engineering ,Vol. 15, 2011, pp.3689-3693.
[13]D. Bertsimas and M. Sim, “Robust discrete optimization and network flows,” Mathematical Programming, Vol. 98, No. 1, 2003, pp. 49-71.
[14]D. Bertsimas and M. Sim, “The Price of Robustness,” Operations Research, Vol. 52, No. 1, 2004, pp. 35-53.
[15]D. V. Veldhuizen and G. Lamont, “Multi-objective evolutionary algorithm test suites,” Proceedings of the 1999 ACM symposium on Applied computing, New York, 1999, pp. 351-357.
[16]F. Akagi, H. Osaki and S. Kikuchi, “The method of analysis of assembly work based on the fastener method,” Japan Society Mechanical Engineering, Vol. 23, No. 184, 1980, pp. 1670-1675.
[17]G. Barbarosoglu and T. Yazgac, “An application of the analytic hierarchy process to the supplier selection problem,” Production and Inventory Management Journal, Vol. 38, No. 1, 1997, pp. 14-21.
[18]G. Boothroyd, P. Dewhurst and W. A. Knight, Production Design for Manufacture and Assembly, 3th Edition, United States:CRC Press, 2010.
[19]G. Claßen, A. M. C. A. Koster and A. Schmeink, “Planning wireless networks with demand uncertainty using robust optimization,” Optimization Online Eprint server, Retrieved June 6, 2011,
http://www.optimization-online.org/DB_HTML/2011/03/2954.html.
[20]G. W. Dickson, “An analysis of vender selection systems and decisions,” Journal of Purchasing, Vol. 2, No. 1, 1966, pp. 5-17.
[21]H. C. B. Oliveira and G. C. Vasconcelos, “A hybrid search method for the vehicle routing problem with time windows,” Annals of Operations Research, Vol. 180, No. 1, 2010, pp. 125-144.
[22]H. Ding, L. Benyoucef and X. Xie, “A simulation optimization methodology for supplier selection problem,” International Journal Computer Integrated Manufacturing, Vol. 18, No. 2-3, 2005, pp. 210-224.
[23]H. E. Tseng and R. K. Li, “A novel means of generating assembly sequences using the connector concept,” Journal of Intelligent Manufacturing, Vol. 10, No. 5, 1999, pp. 423-435.
[24]H. E. Tseng, “An improved ant colony system for assembly sequence planning based on connector concept,” Lecture Notes in Electrical Engineering, Vol. 97, No. 1, 2011, pp. 881-888.
[25]H. E. Tseng, “Guided genetic algorithms for solving the larger constraint assembly problem,” International Journal of Production Research, Vol. 44, No. 3, 2006, pp. 601-625.
[26]H. E. Tseng, J. D. Li and Y. H. Chang, “Connector-based approach to assembly planning using genetic algorithms,” International Journal Production Research, Vol. 42, No. 11, 2004, pp. 2243-2261.
[27]H. F. Wang and H. W. Hsu, “A closed-loop logistic model with a spanning-tree based genetic algorithm,” Computers & Operations Research, Vol. 37, No. 2, 2010, pp. 376-389.
[28]H. Panahi and R. T. Moghaddam, “Solving a multi-objective open shop scheduling problem by a novel hybrid ant colony optimization,” Expert Systems with Applications, Vol.38, No. 3, 2011, pp. 2817-2822.
[29]H. S. Wang, Z. H. Che, “An integrated model for supplier selection decisions in configuration changes,” Expert Systems with Applications, Vol. 32 No. 4, 2007, pp. 1132-1140.
[30]H. Shan, S. Li, D. Gong and P. Lou, “Genetic simulated annealing algorithm-based assembly sequence planning,” International Technology and Innovation Conference, Vol. 524, 2006, pp. 1573-1579.
[31]I. Baybars, “A survey of exact algorithms for the simple assembly line balancing,” Management Science, Vol.32, No. 8, 1986, pp. 909-932.
[32]I. Rojas, J. Gonzalez, H. Pomares, J. J. Merelo, P. A. Castillo and G. Romero, “Statistical analysis of the main parameters involved in the design of a genetic algorithm,” IEEE Transactions on Systems, Man and Cybernetics, Part C, Vol. 32, No. 1, 2002, pp. 31-37.
[33]J. D. Schaffer, “Multiple objective optimization with vector evaluated genetic algorithms,” Proceedings of the First International Conference on Genetic Algorithms, Hillsdale, USA, 1985, pp. 93-100.
[34]J. Horn, N. Nafpliotis and D. E. Goldberg, “A niched pareto genetic algorithm for multiobjective optimization,” Proceedings of the First IEEE Conference on Evolutionary Computation, Vol. 1, 1994, pp. 82-87.
[35]J. Jemai, M. Zekri and K. Mellouli, “An NSGA-II algorithm for the green vehicle routing problem,” Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization, Heidelberg, pp.34-78.
[36]J. M. Mulvey, R. J. Vanderbei and S. A. Zenios, “Robust optimization of large-scale systems,” Operations Research, Vol. 43, No. 2, 1995, pp. 264-281.
[37]J. W. Wang, C. H. Cheng and K. C. Huang, “Fuzzy hierarchical TOPSIS for supplier selection,” Applied Soft Computing, Vol. 9, No. 1, 2009, pp. 377-386.
[38]K. Deb, A. Pratap, S. Agarwal and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, Vol. 6, No. 2, 2002, pp. 182-197.
[39]K. Ghoseiri and S. F. Ghannadpour, “Multi-objective vehicle routing problem with time windows using goal programming and genetic algorithm,” Applied Soft Computing, Vol. 10, No. 4, 2010, pp. 1096-1107.
[40]K. S. Park, “Efficiency bounds and efficiency classifications in DEA with imprecise data,” Journal of the Operational Research Society, Vol. 58, No. 4, 2007, pp. 533-540.
[41]L. D’Acierno, M. Gallo and B. Montella, “An Ant Colony Optimisation algorithm for solving the asymmetric traffic assignment problem,” European Journal of Operational Research, Vol. 217, 2012, pp. 459-469.
[42]L. Gao, W. Qian, X. Li and J. F. Wang, “Application of memetic algorithm in assembly sequence planning,” International Journal of Advanced Manufacturing Technology, Vol. 49, No. 9-12, 2010 ,pp. 1175-1184.
[43]L. Ozbakir, A. Baykasoglu, B. Gorkemli and L. Gorkemli, “Multiple-colony ant algorithm for parallel assembly line balancing problem,” Applied Soft Computing, Vol. 11, No. 3, 2011, pp. 3186-3198.
[44]M. A. Figliozzi, “An iterative route construction and improvement algorithm for the vehicle routing problem with soft-time windows,” Transportation Research Part C: Emerging Technologies, Vol. 18, No. 5, 2010, pp. 668-679.
[45]M. A. Vonderembse and M. Tracey, “The impact of supplier selection criteria and supplier involvement on manufacturing performance,” The Journal of Supply Chain Management, Vol. 35, No. 3, 1999, pp. 33-39.
[46]M. Dorigo and L. M. Gambardella, “Ant Colony System: A cooperative learning approach to the traveling salesman problem,” IEEE Transactions on Evolutionary Computation, Vol.1, No.1, 1997, pp. 53-66.
[47]M. Dorigo, A. Colorni and V. Maniezzo, “An investigation of some properties of an ant algorithm,” Proceedings of the Parallel Problem Solving from Nature Conference, Vol. 2, 1992, pp. 509-520.
[48]M. Dorigo, G.D. Caro and L.M. Gambardella, “Ant algorithms for discrete optimization,” Artificial Life, Vol. 5, 1999, pp.137-172.
[49]M. F. F. Rashid, W. Hutabarat and T. Ashutosh, “A review on assembly sequence planning and assembly line balancing optimization using soft computing approaches,” International Journal of Advanced Manufacturing Technology, Vol. 5, No. 1-4, 2012, pp. 335-349.
[50]M. Kumar, P. Vrat and R. Shankar, “A fuzzy programming approach for vendor selection problem in a supply chain,” International Journal of Production Economics, Vol. 101, No. 2, 2006, pp. 273-285.
[51]M. M. Solomon, “Algorithms for the vehicle routing and scheduling problems with time window constraints,” Operations Research, Vol. 35, No. 2, 1987, pp. 254-265.
[52]M. S. Pishvaee, M. Rabbani and S. A. Torabi, “A robust optimization approach to closed-loop supply chain network design under uncertainty,” Applied Mathematical Modelling, Vol. 35, No. 2, 2011, pp. 637-649.
[53]N. Boysen, M. Fliedner and A. Scholl, “Assembly line balancing: which model to use when? ,” International Journal of Production Economics, Vol. 111, No. 2, 2006, pp. 509-528.
[54]N. Christofides, A. Mingozzi and E. Toth, “State space relaxation procedures for the computation of bounds to routing problems,” Networks, Vol. 11, No. 2, 1981, pp. 145-164.
[55]N. Srinivas and K. Deb, “Multiobjective optimization using nondominated sorting in genetic algorithms,” Evolutionary Computation, Vol. 2, No. 3, 1994, pp. 221-248.
[56]N. V. Sahinidis, “Optimization under uncertainty: state-of-the-art and opportunities,” Computers and Chemical Engineering, Vol. 28, No. 6-7, 2004, pp. 971-983.
[57]P. Chutima and P. Chimklai, “Multi-objective two-sided mixed-model assembly line balancing using particle swarm optimisation with negative knowledge,” Computers & Industrial Engineering, Vol. 62, No. 1, 2012, pp. 39-55.
[58]Q. H. Wu and Y. J. Cao, “Stochastic optimization of control parameters in genetic algorithms,” IEEE International Conference on Evolutionary Computation, Vol. 13, No. 16, 1997, pp. 77-80.
[59]R. B. Taha, A. K. El. Kharbotly, Y. M. Sadek and N. H. Afia, “A Genetic Algorithm for solving two-sided assembly line balancing problems,” Ain Shams Engineering Journal, Vol. 2, No. 3-4, 2011, pp. 227-240.
[60]R. Verma and M. E. Pullman, “An analysis of the supplier selection process,” International Journal of Management Science, Vol. 26, No. 6, 1998, pp. 739-750.
[61]S. Cao and K. Zhang, “Optimization of the flow distribution of e-waste reverse logistics network based on NSGA II and TOPSIS,” International Conference on E -Business and E –Government, Shanghai, China, 2011, pp. 1-5.
[62]S. Dowlatshahi, “Designer-buyer-supplier interface: Theory versus practice,” International Journal of Production Economics, Vol. 63, No. 2, 2000, pp. 111-130.
[63]S. H. Ghodsypour and C. O’Brien, “The total cost of logistics in supplier selection, under conditions of multiple sourcing, multiple criteria and capacity constraints,” International Journal of Production Economics, Vol. 73, No. 1, pp. 15-27.
[64]S. M. J. Mirzapour, Al-e-hashem, H. Maleklyand and M. B. Aryanezhad, “A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty,” International Journal of Production Economics, Vol. 134, No. 1, 2011, pp. 28-42.
[65]S. Önüt, S. S. Kara and E. Işik, “Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company, ” Expert Systems with Applications, Vol. 36, No. 2, 2009, pp. 3887-3895.
[66]S. Talluri and J. Sarkis, “A model for performance monitoring of suppliers,” International Journal of Production Research, Vol. 40, No. 16, 2002, pp. 4257-4269.
[67]T. Hasuike and H. Ishii, “Robust portfolio selection problems including uncertainty factors,” IAENG International Journal of Applied Mathematics, Vol. 38, No. 3, 2008, pp. 151-157.
[68]T. Kellegöz and B. Toklu, “An efficient branch and bound algorithm for assembly line balancing problems with parallel multi-manned workstations,” Computers & Operations Research, Vol. 39, No. 12, 2012, pp. 3344-3360.
[69]T. L. De Fazio and D. E. Whitney, “Simplified generation of all mechanical assembly sequence,” IEEE Journal of Robotics and Automations, Vol. 3, No. 6, 1987, pp. 640-658.
[70]T. R. Sexton and Y. M. Choi, “Pickup and delivery of partial loads with soft time windows,” American Journal of Mathematical and Management Sciences, Vol. 6, No. 3-4, 1986, pp. 369-398.
[71]T. Stützle and H. H. Hoos, “MAX–MIN Ant System and local search for the traveling salesman problem,” IEEE International Conference on Evolutionary Computation, Indiana, U.S.A., 1997, pp. 308-313.
[72]W. Ho, X. Xu and P. K. Dey, “Multi-criteria decision making approaches for supplier evaluation and selection: A literature review, ”European Journal of Operational Research, Vol. 202, No. 1, 2010, pp. 16-24.
[73]X. D. Zhang, G.H. Huang, C. W. Chan, Z. F. Liu and Q. G. Lin, “A fuzzy-robust stochastic multiobjective programming approach for petroleum waste management planning,” Applied Mathematical Modelling, Vol. 34, No. 10, 2010, pp. 2778-2788.
[74]Y. Wang and J. H. Liu, “Chaotic particle swarm optimization for assembly sequence planning,” Robotics and Computer-Integrated Manufacturing, Vol. 26, No. 2, 2010, pp. 212-222.
[75]Z. J. Lee, S. T. Chou, C. Y. Lee and S. W. Lin, “A hybrid approach for vehicle routing problem with time windows,” Advances in Intelligent Transportation Systems, Vol. 1, No. 1, 2012, pp. 11-18.
[76]Z. Li and M. G. Ierapetritou, “Robust optimization for process scheduling under uncertainty,” Industrial and Engineering Chemistry Research, Vol. 47, No. 12, 2008, pp. 4148-4157.


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