跳到主要內容

臺灣博碩士論文加值系統

(44.220.62.183) 您好!臺灣時間:2024/03/01 21:23
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:毛俊彬
研究生(外文):Chun-Pin Mao
論文名稱:應用蟻群最佳化演算法於含時窗限制之旅行推銷員問題
論文名稱(外文):Applying Ant Colony Optimization in Solving the Traveling Salesman Problem with Time Windows
指導教授:鄭啟斌鄭啟斌引用關係
指導教授(外文):Chi-Bin Cheng
學位類別:碩士
校院名稱:朝陽科技大學
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:2006
畢業學年度:94
語文別:中文
論文頁數:68
中文關鍵詞:含時窗限制之旅行推銷員問題旅行推銷員問題蟻群最佳化
外文關鍵詞:Ant Colony OptimizationTraveling Salesman Problem with Time WindowsTraveling Salesman Problems
相關次數:
  • 被引用被引用:19
  • 點閱點閱:608
  • 評分評分:
  • 下載下載:117
  • 收藏至我的研究室書目清單書目收藏:1
含時窗限制之旅行推銷員問題定義為:找到一組最小成本路徑,使所有城市皆被服務一次,且必須符合各個城市之時窗限制。在實務上有許多重要問題,如生產排程與車輛途程等皆為含時窗限制之旅行推銷員問題之應用。學者Savelsberg(1985) 證實含時窗限制之旅行推銷員問題屬於NP-complete,若以最佳化解法求解缺乏效率,因此如何發展近似解法快速求得較佳解愈來愈受到重視。近年來由自然界現象所啟迪之蟻群最佳化演算法,已被證實在求解旅行推銷員問題有良好之績效。本研究利用蟻群最佳化求解旅行推銷員問題之優點,並在局部啟發式函數上作修改,使其適用於含時窗限制之旅行推銷員問題。經例題測試與比較,結果顯示本研究演算法在窄時間窗例題上有不錯之成效,且可在小節點數少的例題上得到最佳解。
The traveling salesman problem with time windows (TSPTW) is a problem of finding a minimum cost tour where all cities must be visited exactly once within their requesting time windows. This problem has important applications in practice such as scheduling and routing problems. Savelsberg (1985) showed that simply finding a feasible solution of TSPTW is NP-complete. Traditional optimization algorithms generally need exponential computation time in solving such a problem. Thus, the development of approximate algorithms has received more and more attention in recent years. Ant colony optimization (ACO) is one of the most recent methods inspired by biological behavior for developing approximate algorithms. It has been shown to be efficient to solve traveling salesman problems. In this research, a modified meta-heuristic based on ACO is applied to solve the TSPTW. Testing results on benchmark instances demonstrate that the proposed approach performs well on problem instances with narrower time windows; in particular, optimum solutions are found for some small-scale problems.
摘要 I
ABSTRACT II
誌謝 III
目錄 IV
表目錄 VII
圖目錄 IX
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研究步驟與流程 4
第二章 文獻探討 7
2.1旅行推銷員問題 7
2.2時間窗 11
2.3TSP與TSPTW之求解方法 13
2.4蟻群最佳化 18
第三章 研究方法 23
3.1問題描述及基本假設 23
3.1.1 問題描述 23
3.1.2 基本假設 26
3.2演算法架構 27
3.2.1 蟻群系統 28
3.2.2 型局部啟發式函數 31
3.2.3 演算法步驟流程 34
第四章 參數設定與例題測試 38
4.1測試題庫 38
4.2參數設定 39
4.2.1螞蟻數量 39
4.2.2狀態轉移規則決策參數 40
4.2.3費洛蒙衰退參數 41
4.2.4 型函數控制參數 42
4.2.5 型函數控制參數 42
4.2.6局部啟發式函數比重參數 43
4.2.7局部啟發式函數比重參數 44
4.3例題測試與比較分析 45
第五章 結論與建議 54
5.1結論 54
5.2建議 55
參考文獻 56
附錄一 67
[1] Ascheuer, N., Fischetti, M., and Grötschel, M., “Solving asymmetric traveling salesman problem with time windows by branch-and-cut,” Mathematical Programming, Vol. 90, pp.475-506(2001).
[2] Baker, E., “An exact algorithm for the time constrained traveling salesman problem,” Operations Research, Vol. 31, pp.938-945(1983).
[3] Balas, E., and Simonetti, N., “Linear time dynamic programming algorithms for new classes of restricted TSPs: a computational study,” INFORMS Journal on Computing, Vol. 13, pp.56-75(2001).
[4] Bauer, A., Bullnheimer, B., Hartl, R. F., and Strauss, C., “An ant colony optimization approach for the single machine total tardiness problem,” In Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), IEEE Press, Piscataway, NJ, pp.1445-1450(1999).
[5] Blum, C., “Ant colony optimization: Introduction and recent trends,” Physics of Life Reviews, Vol. 2, No. 4, pp.353-373(2005).
[6] Bonabeau,E., Henaux, F., Guérin, S., Snyers, D., Kuntz, P., and Theraulaz, G.., “Routing in telecommunication networks with “Smart” ant-like agents,” In Proceedings of IATA’98, Second Int. Workshop on Intelligent Agents for Telecommunication Applications, Lectures Notes in AI Vol. 1437, Springer Verlag(1998).
[7] Bräysy, O., and Gendreau, M., “Vehicle routing problem with time windows, part I: Route construction and local search algorithms,” Transportation Science, Vol. 39, No.1, pp.104-118 (2005).
[8] Bräysy, O., and Gendreau, M., “Vehicle routing problem with time windows, part II: Metaheuristics,” Transportation Science, Vol. 39, No.1, pp.119-139 (2005).
[9] Bullnheimer, B., Hartl, R. F., and Strauss, C., “A new rank-based version of the Ant System: A computational study,” Central European Journal for Operations Research and Economics, Vol. 7, No. 1, pp.25-38(1999).
[10] Bullnheimer, B., Hartl, R. F., and Strauss, C., “An improved ant system algorithm for the vehicle routing problem,” Annals of Operations Research, Vol. 89, pp.319-328(1999)
[11] Bullnheimer, B., Hartl, R. F., and Strauss, C., “Applying the Ant System to the vehicle routing problem,” In Voß, S., Martello, S., Osman, I. H., and Roucairol, C., editors, Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimization, Kluwer Academic Publishers, Dordrecht, pp.285-296(1999).
[12] Christofides, N., Mingozzi, A., and Toth, P., “State space relaxation procedures for the computation of bounds to routing problems,” Networks, Vol. 11, pp.145-146(1981).
[13] Colorni, A., Dorigo, M., Maniezzo, V., and Trubian, M., “Ant System for jobshop scheduling,” JORBEL-Belgian Journal of Operations Research, Statistics and Computer Science, Vol. 34, No. 1, pp.39-53(1994).
[14] Cordón, O., Fernández de Viana, I., Herrera, F., and Moreno, L., “A new ACO model integrating evolutionary computation concepts: The best-worst ant system,” In Dorigo, M., Middendorf, M., and Stützle, T., editors, Abstract proceedings of ANTS2000 - From Ant Colonies to Artificial Ants: A Series of International Workshops on Ant Algorithms, Université Librede Bruxelles, pp.22-29(2000).
[15] Costa, D., and Hertz, A., “Ants can colour graphs,” Journal of the Operational Research Society, Vol. 48, pp.295-305(1997).
[16] den Besten, M., Stützle, T., and Dorigo, M., “Ant colony optimization for the total weighted tardiness problem,” In Schoenauer, M., Deb, K., Rudolph, G., Yao, X., Lutton, E., Merelo, J. J., and Schwefel, H. S., editors, Proceedings of PPSN-VI, Sixth International Conference on Parallel Problem Solving from Nature, volume 1917 of Lecture Notes in Computer Science, Springer Verlag, Berlin, Germany, pp. 611-620(2000).
[17] Di Caro, G., and Dorigo, M., “AntNet: A mobile agents approach to adaptive routing,” Technical Report IRIDIA/97-12, IRIDIA, Université Libre de Bruxelles, Belgium(1997).
[18] Di Caro, G., and Dorigo, M., “AntNet: Distributed stigmergetic control for communications networks,” Journal of Artificial Intelligence Research, Vol. 9, pp. 317-365(1998).
[19] Di Caro, G., and Dorigo, M., “Extending AntNet for best-effort Quality-of-Service routing,” Unpublished presentation at ANTS’98 - From Ant Colonies to Artificial Ants: First International Workshop on Ant Colony Optimization http://iridia.ulb.ac.be/ants98/ants98.html, October 15-16(1998).
[20] Di Caro,G., and Dorigo, M., “Two ant colony algorithms for best-effort routing in datagram networks,” In Pan, Y., Akl, S. G., and Li, K., editors, Proceedings of the Tenth IASTED International Conference on Parallel and Distributed Computing and Systems (PDCS’98), IASTED/ACTA Press, Anheim, pp.541-546(1998).
[21] Dorigo, M., “Optimization, Learning and Natural Algorithms (in Italian),” Ph.D. Dissertation, Dipartimento di Elettronica, Politecnico di Milano, Italy(1992).
[22] Dorigo, M., and Gambardella, L. M., “Ant colonies for the traveling salesman problem,” BioSystems, Vol. 43,pp.73-81(1997).
[23] Dorigo, M., and Gambardella, L. M., “Ant Colony System: A cooperative learning approach to the traveling salesman problem,” IEEE Transactions on Evolutionary Computation, Vol. 1, No. 1, pp.53-66(1997).
[24] Dorigo, M., and Stützle, T., “The ant colony optimization metaheuristic: Algorithms, applications, and advances,” In Glover, F., and Kochenberger, G., editors, Handbook of Metaheuristics, International Series in Operations Research and Management Science, Kluwer, Boston, MA, pp.251-285(2002).
[25] Dorigo, M., Maniezzo, V., and Colorni, A., “Positive feedback as a search strategy,” Technical Report 91-016, Dipartimento di Elettronica, Politecnico di Milano, Italy(1991).
[26] Dorigo, M., Maniezzo, V., and Colorni, A., “The Ant System: Optimization by a colony of cooperating agents,” IEEE Transactions on Systems, Man, and Cybernetics - Part B, Vol. 26, No. 1, pp.29-41(1996).
[27] Dumas, Y., Desrosiers, J., Gélinas, É., and Solomon, M. M., “An optimal algorithm for the traveling salesman problem with time windows,” Operations Research, Vol. 43, No. 2, pp.367-371(1995).
[28] Gambardella, L. M., and Dorigo, M., “HAS-SOP: An hybrid Ant System for the sequential ordering problem,” Technical Report IDSIA-11-97, IDSIA, Lugano, Switzerland(1997).
[29] Gambardella, L. M., and Dorigo, M., “Solving symmetric and asymmetric TSPs by ant colonies,” In Proceedings of the 1996 IEEE International Conference on Evolutionary Computation (ICEC’96), IEEE Press, Piscataway, NJ, pp.622-627(1996).
[30] Gambardella, L. M., and Dorigo., M., “Ant Colony System hybridized with a new local search for the sequential ordering problem,” INFORMS Journal on Computing, Vol. 13, No. 3, pp.237-255(2000).
[31] Gambardella, L. M., and Dorigo., M., “Ant-Q: A reinforcement learning approach to the traveling salesman problem,” In Prieditis, A., and Russell, S., editors, Proceedings of the Twelfth International Conference on Machine Learning (ML-95), Morgan Kaufmann Publishers, Palo Alto, CA, pp.252-260(1995).
[32] Gambardella, L. M., Taillard, É. D., and Agazzi, G., “MACS-VRPTW: A multiple ant colony system for vehicle routing problems with time windows,” In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, McGraw Hill, London, UK, pp.63-76(1999).
[33] Gambardella, L. M., Taillard, É. D., and Dorigo, M., “Ant colonies for the quadratic assignment problem,” Journal of the Operational Research Society, Vol. 50, No. 2, pp.167-176(1999).
[34] Gendreau, M., Hertz, A., Laporte, G., and Stan, M., “A generalized insertion heuristic for the traveling salesman problem with time windows,” Operations Research, Vol. 4, No. 3, pp.330-335(1998).
[35] Heusse, M., Gu´erin, S., Snyers, D., and Kuntz, P., “Adaptive agent-driven routing and load balancing in communication networks,” Technical Report RR-98001-IASC, D´epartment Intelligence Artificielle et Sciences Cognitives, ENST Bretagne(1998).
[36] Langevin, A., Desrochers, M., Desrosiers, J., and Soumis, F., “A two-commodity flow formulation for the traveling salesman and makespan problems with time windows,” Networks, Vol. 23, pp.631-640(1993).
[37] Leguizamón, G., and Michalewicz, Z., “A new version of Ant System for subset problems,” In Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), IEEE Press, Piscataway, NJ, pp.1459-1464(1999).
[38] Liang, Y.-C., and Smith, A. E., “An Ant System approach to redundancy allocation,” In Proceedings of the 1999 Congress on Evolutionary Computation, IEEE Press, Piscataway, NJ, pp.1478-484(1999).
[39] Maniezzo, V., “Exact and approximate nondeterministic tree-search procedures for the quadratic assignment problem,” INFORMS Journal on Computing, Vol. 11, No. 4, pp.358-369(1999).
[40] Maniezzo, V., and Carbonaro, A., “An ANTS heuristic for the frequency assignment problem,” Future Generation Computer Systems, Vol. 16, No. 8, pp.927-935(2000).
[41] Maniezzo, V., and Colorni, A., “The Ant System applied to the quadratic assignment problem,” IEEE Transactions on Data and Knowledge Engineering, Vol. 11, No. 5, pp.769-778(1999).
[42] Maniezzo, V., Colorni, A., and Dorigo, M., “The Ant System applied to the quadratic assignment problem,” Technical Report IRIDIA/94-28, IRIDIA, Universit´e Libre de Bruxelles, Belgium(1994).
[43] Merkle, D., Middendorf, M., and Schmeck, H., “Ant colony optimization for resource-constrained project scheduling,” In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000), Morgan Kaufmann Publishers, San Francisco, CA, pp.893-900(2000).
[44] Michel, R., and Middendorf, M., “An ACO algorithm for the shortest super-sequence problem,” In Corne, D., Dorigo, M., and Glover, F., editors, New Ideas in Optimization, pages 51–61. McGraw Hill, London, UK(1999).
[45] Michel, R., and Middendorf, M., “An island model based Ant System with lookahead for the shortest supersequence problem,” In Eiben, A. E., Bäck, T., Schoenauer, M., and Schwefel, H.-P., editors, Proceedings of PPSN-V, Fifth International Conference on Parallel Problem Solving from Nature, volume1498 of Lecture Notes in Computer Science, Springer Verlag, Berlin, Germany, pp.692-701(1998).
[46] Mingozzi, A., Bianco, L., and Ricciardelli, S., “Dynamic programming strategies for the traveling salesman problem with time windows and precedence constraints,” Operations Research, Vol. 45, pp.365-377(1997.)
[47] Navarro Varela, G., and Sinclair, M. C., “Ant colony optimisation for virtual-wavelength-path routing and wavelength allocation,” In Proceedings of the 1999 Congress on Evolutionary Computation (CEC’99), IEEE Press, Piscataway, NJ, pp.1809-1816(1999).
[48] Pesant, G., Gendreau, M., Potvin, J.-Y., Rousseau, J.M., “An exact constraint logic programming algorithm for the traveling salesman problem with time windows,” Transportation Science, Vol. 32, pp.12-29(1998).
[49] Potvin, J.-Y., and Bengio, S., “The vehicle routing problem with time windows- part II: genetic search,” INFORMS Journal on Computing, Vol. 8, pp.165-172(1996).
[50] Ramalhinho Lourenço, H., and Serra, D., “Adaptive approach heuristics for the generalized assignment problem,” Technical Report Technical Report Economic Working Papers Series No.304, Universitat Pompeu Fabra, Dept. of Economics and Management, Barcelona, Spain(1998).
[51] Savelsbergh, M. W. P., “Local search in routing problems with time windows,” Annals of Operations Research, Vol. 4, pp.285-305(1985).
[52] Savelsbergh, M. W. P., “The vehicle routing problem with time windows: Minimizing route duration,” ORSA Journal on Computing, Vol. 4, pp. 146-154(1992).
[53] Schoonderwoerd, R., Holland, O., and Bruten, J., “Ant-like agents for load balancing in telecommunications networks,” In Proceedings of the First International Conference on Autonomous Agents, ACM Press, pp.209-216(1997).
[54] Schoonderwoerd, R., Holland, O., Bruten, J., and Rothkrantz, L., “Ant-based load balancing in telecommunications networks,” Adaptive Behavior, Vol. 5, No. 2, pp.169-207(1996).
[55] Solnon, C., “Solving permutation constraint satisfaction problems with artificial ants,” In Horn, W., editor, Proceedings of the 14th European Conference on Artificial Intelligence, IOS Press, Amsterdam, The Netherlands, pp.118-122(2000).
[56] Solomon, M. M., “Alorithms for the vehicle routing and scheduling problems with time windows constraints,” Operation research, Vol. 35, No. 2, pp.254-265(1987).
[57] Stützle, T., “An ant approach to the flow shop problem,” In Proceedings of the 6th European Congress on Intelligent Techniques & Soft Computing (EUFIT’98), Verlag Mainz, Aachen, Vol. 3, pp.1560-1564(1998).
[58] Stützle, T., “MAX-MIN Ant system for the quadratic assignment problem,” Technical Report AIDA-97-4, FG Intellellektik, FB Informatik, TU Darmstadt, July(1997).
[59] Stützle, T., and Dorigo, M., “ACO Algorithms for the Traveling Salesman Problem,” In Miettinen, K., Makela, M., Neittaanmaki, P., Periaux, J., editors, Evolutionary Algorithms in Engineering and Computer Science, John Wiley & Sons, Chichester, UK, pp.163-183(1999).
[60] Stützle, T., and Hoos, H. H., “The MAX-MIN Ant System and local search for the traveling salesman problem,” In Bäck, T., Michalewicz, Z., and Yao, X., editors, Proceedings of the 1997 IEEE International Conference on Evolutionary Computation (ICEC’97), IEEE Press, Piscataway, NJ, pp.309-314(1997).
[61] Stützle, T., and Hoos, H.H., “MAX–MIN Ant system,” Future Generat Comput Syst, Vol. 16, No. 8, pp.889–914(2000).
[62] Stützle, T., Local Search Algorithms for Combinatorial Problems: Analysis, Improvements, and New Applications, Infix, Sankt Augustin, Germany(1999).
[63] Subramanian, D., Druschel, P., and Chen, J., “Ants and reinforcement learning: A case study in routing in dynamic networks,” In Proceedings of IJCAI-97, International Joint Conference on Artificial Intelligence, Morgan Kaufmann, pp.832-838(1997).
[64] van der Put, R., “Routing in the faxfactory using mobile agents,” Technical Report R&D-SV-98-276, KPN Research(1998).
[65] White, T., Pagurek, B., and Oppacher, F., “Connection management using adaptive mobile agents,” In Arabnia, H.R., editor, Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications (PDPTA’98), CSREA Press, pp.802-809(1998).
[66]王保元,「物流中心冷凍食品配送模式之研究」,碩士論文,朝陽大學工業工程與管理研究所,台中(2000)。
[67]王耿彬,「應用遺傳演算法於低溫冷凍物流中心之車輛配送排程規劃」,碩士論文,朝陽大學工業工程與管理研究所,台中(2001)。
[68]王瑞吟,「改良式EBGA演算法於推銷員旅行問題(TSP)之研究」,碩士論文,高雄師範大學數學研究所,高雄(2000)。
[69]朱文正,「考量旅行時間可靠度之車輛途程問題─螞蟻族群演算法之應用」,碩士論文,交通大學交通運輸研究所,新竹(2003)。
[70]吳志盛,「啟發式演算法於最佳化與分群問題之研究」,碩士論文,朝陽科技大學資訊管理研究所,台中(2003)。
[71]吳育盈,「改良式蟻拓尋優法求解旅行者推銷員問題」,碩士論文,中華大學科技管理研究所,新竹(2004)。
[72]李洪鑫,「含時間窗車輛途程問題各演算法適用範圍之探討」,碩士論文,東海大學工業工程研究所,台中(2000)。
[73]周淑蓉,「以群聚及禁制搜尋法求解含時窗限制之車輛巡迴路線問題」,碩士論文,朝陽科技大學資訊管理研究所,台中(2004)。
[74]周蘇江,「含時窗限制的動態車輛途程問題之研究」,碩士論文,中原大學工業工程研究所,台中(2001)。
[75]林依潔,「整合模糊理論與螞蟻演算法於含時窗限制之車輛途程問題」,碩士論文,台北科技大學生產系統工程與管理研究所,台北(2003)。
[76]林惠民,「具時窗之多趟次車輛途程問題」,碩士論文,元智大學資訊管理研究所,桃園(2002)。
[77]高秀梅,「蟻群最佳化演算法於時窗限制之車輛途程問題的研究」,碩士論文,元智大學工業工程與管理研究所,桃園(2003)。
[78]張寶豐,「以複合啟發式演算法求解時窗限制車輛途程問題」,碩士論文,中原大學工業工程研究所,桃園(2003)。
[79]許再豐,「即時資訊下動態車輛途程規劃研究」,碩士論文,朝陽科技大學工業工程與管理系研究所,台中(2004)。
[80]許晉嘉,「宅配業貨物配送路線規劃問題之研究」,碩士論文,成功大學交通管理研究所,台南(2003)。
[81]陳百傑,「以啟發式演算法求解時窗限制車輛途程問題」,碩士論文,中原大學工業工程研究所,桃園(2002)。
[82]陳怡芳,「單一宅配車輛路線規劃問題之研究」,碩士論文,逢甲大學交通工程與管理研究所,台中(2005)。
[83]陳契伸,「硬性軟性時窗限制之車輛途程問題研究」,碩士論文,中原大學工業工程研究所,桃園(2001)。
[84]陳建緯,「大規模旅行推銷員問題之研究:鄰域搜尋法與巨集啟發式解法之應用」,碩士論文,交通大學運輸工程與管理研究所,新竹(2001)。
[85]陳凱,「族類競爭演算法在物流中心車輛分派問題的應用與測試之研究」,碩士論文,輔仁大學資訊管理研究所,台北(2004)。
[86]陳隆熙,「一個解決TSP問題最佳解的穩定方法─以TA演算法為例」,碩士論文,大葉大學工業工程研究所,彰化(2002)。
[87]陳衛群,「滿足三角不等式之旅行者推銷員問題的分支界定解法研究」,碩士論文,清華大學資訊工程研究所,新竹(2001)。
[88]曾筠予,「以拉式鬆弛演算法求解車輛定線問題」,碩士論文,國立交通大學運輸科技與管理研究所,新竹(2005)。
[89]楊雅惠,「供應鏈網路下整合存貨管理與車輛途程設計之研究」,碩士論文,國立東華大學企業管理研究所,花蓮(2004)。
[90]熊碩成,「以實驗設計改善時窗限制下物流中心車輛途程問題之研究」,碩士論文,國防管理學院資源管理研究所,台北(2001)。
[91]蔡志強,「以蟻群系統建立物流宅配最佳化配送路徑規劃」,碩士論文,屏東科技大學工業管理研究所,屏東(2004)。
[92]盧步雲,「應用塔布搜尋法於含軟性時窗限制之動態需求撿取配送途程規劃問題」,碩士論文,中原大學工業工程研究所,桃園(2002)。
[93]蕭宗勝,「螞蟻族群演算法應用在組合問題之研究」,碩士論文,銘傳大學資訊管理研究所,桃園(2002)。
[94]羅中育,「田口品質工程應用於模擬退火法參數組合─以旅行推銷員問題(TSP)為例」,碩士論文,雲林科技大學工業工程與管理研究所,雲林(2001)。
[95]羅文光,「螞蟻演算法應用於最佳化路徑演算」,碩士論文,元智大學電機工程研究所,桃園(2004)。
[96]羅敏華,「蟻群最佳化演算法於載重限制之車輛途程問題的研究」,碩士論文,元智大學工業工程與管理研究所,桃園(2003)。
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
無相關期刊