Skip navigation

DSpace JSPUI

DSpace preserves and enables easy and open access to all types of digital content including text, images, moving images, mpegs and data sets

Learn More
DSpace logo
English
中文
  • Browse
    • Communities
      & Collections
    • Publication Year
    • Author
    • Title
    • Subject
    • Advisor
  • Search TDR
  • Rights Q&A
    • My Page
    • Receive email
      updates
    • Edit Profile
  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊工程學系
Please use this identifier to cite or link to this item: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68497
Full metadata record
???org.dspace.app.webui.jsptag.ItemTag.dcfield???ValueLanguage
dc.contributor.advisor呂育道(Yuh-Dauh Lyuu)
dc.contributor.authorYu-Chuan Liuen
dc.contributor.author劉育全zh_TW
dc.date.accessioned2021-06-17T02:23:02Z-
dc.date.available2021-08-24
dc.date.copyright2017-08-24
dc.date.issued2017
dc.date.submitted2017-08-19
dc.identifier.citationArora, S. (1997). Nearly linear time approximation schemes for Euclidean TSP and other geometric problems. In Proceedings of 38th Symposium on Foundations of Computer Science, 1997, Miami Beach, Florida, pages 554–563.
Christofides, N. (1976). Worst-case analysis of a new heuristic for the travelling salesman problem. Technical Report 388, Graduate School of Industrial Administration, Carnegie Mellon University, Pittsburgh.
Croes, G. A. (1958). A method for solving traveling-salesman problems. Operations Research, 6(6):791–812.
Drake, D. E., and Hougardy, S. (2003a). Linear time local improvements for weighted matchings in graphs. In Proceedings of 2nd International Workshop on Experimental and Efficient Algorithms, 2003, Ascona, Switzerland, pages 107–119.
Drake, D. E., and Hougardy, S. (2003b). A simple approximation algorithm for the weighted matching problem. Information Processing Letters, 85(4):211–213.
Duan, R., and Pettie, S. (2010). Approximating maximum weight matching in near-linear time. In Proceedings of 51st Symposium on Foundations of Computer Science, 2010, Las Vegas, pages 673–682.
Duan, R., and Pettie, S. (2014). Linear-time approximation for maximum weight matching. Journal of the ACM, 61(1):1.
Edmonds, J. (1965). Paths, trees, and flowers. Canadian Journal of Mathematics, 17(3):449–467.
Gabow, H. N. (1974). Implementation of algorithms for maximum matching on nonbipartite graphs. Department of Computer Science, Stanford University.
Gabow, H. N. (1990). Data structures for weighted matching and nearest common ancestors with linking. Department of Computer Science, University of Colorado, Boulder.
Gabow, H. N., Galil, Z., and Spencer, T. H. (1984). Efficient implementation of graph algorithms using contraction. In Proceedings of 25th Symposium on Foundations of Computer Science, 1984, Singer Island, Florida, pages 347–357.
Galil, Z., Micali, S., and Gabow, H. (1986). An O(EVlogV) algorithm for finding a maximal weighted matching in general graphs. SIAM Journal on Computing, 15(1):120–130.
Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220(4598):671–680.
Lawler, E. L. (2001). Combinatorial optimization: networks and matroids. Holt, Rinehart, and Winston, New York.
Lin, S., and Kernighan, B. W. (1973). An effective heuristic algorithm for the traveling salesman problem. Operations Research, 21(2):498–516.
Lin, S. (1965). Computer solutions of the traveling salesman problem. Bell System Technical Journal, 44(10):2245–2269.
Pettie, S., and Sanders, P. (2004). A simpler linear time 2/3- ε approximation for maximum weight matching. Information Processing Letters, 91(6):271–276.
Preis, R. (1999). Linear time 1/2-approximation algorithm for maximum weighted matching in general graphs. In Proceedings of Symposium on Theoretical Aspects of Computer Science, 1999, Trier, Germany, pages 259–269.
Reingold, E. M., and Tarjan, R. E. (1981). On a greedy heuristic for complete matching. SIAM Journal on Computing, 10(4):676–681.
Vaidya, P. M. (1989). Geometry helps in matching. SIAM Journal on Computing,
18(6):1201–1225.
Varadarajan, K. R. (1998). A divide-and-conquer algorithm for min-cost perfect matching in the plane. In Proceedings of 39th Symposium on Foundations of Computer Science, 1998, Palo Alto, California, pages 320–329.
Varadarajan, K. R., and Agarwal, P. K. (1999). Approximation algorithms for bipartite and non-bipartite matching in the plane. In Proceddings of Symposium on Discrete Algorithms, 1999, Baltimore, pages 805–814.
Vazirani, V. V. (2013). Approximation algorithms. Springer Science & Business Media.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/68497-
dc.description.abstract在本論文中,我們對於平面上的最小權完美匹配問題提出了幾個不同的啟發式演算法。基於座標平面上的三角不等式性質,提出一個先隨機一組完美匹配並優化它的 local search 演算法,接著在這個算法的基礎上做出許多的改進,最後得出數個還不錯的演算法,在實務上有的可以在和 Blossom 演算法相比下加速數十倍的情況下找出和最佳解誤差不到 2% 的解,或著是在加速數倍的情況下找出誤差 0.5% 左右的的解。zh_TW
dc.description.abstractIn this thesis, we provide some heuristic algorithms for minimum-weight perfect matching problem on a plane. First, we provide a local search algorithm based on triangle inequality. Then we try many methods to improve this algorithm. Finally we get some good algorithms. One can be 20-30 times faster than Blossom algorithm with 2% error and other one can be 3-4 times faster than Blossom algorithm with 0.5% error.en
dc.description.provenanceMade available in DSpace on 2021-06-17T02:23:02Z (GMT). No. of bitstreams: 1
ntu-106-R04922040-1.pdf: 684297 bytes, checksum: 5e75246bbd02d10ec51c8c2c3eace694 (MD5)
Previous issue date: 2017
en
dc.description.tableofcontents口試委員會審定書 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . i
誌謝 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii
摘要 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii
Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv
目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v
圖目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
表目錄 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . viii
第一章 緒論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 研究動機 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 研究目的與方法 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.3 相關研究 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1.3.1 一般圖最大(最小)權匹配 . . . . . . . . . . . . . . . . . . . 2
1.3.2 平面上的最小權匹配 . . . . . . . . . . . . . . . . . . . . . . . 3
1.4 論文架構 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
第二章 演算法與實驗分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1 2-opt . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 匹配合併 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.3 模擬退火 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.4 動態找環 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4.1 動態找環 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14
2.4.2 動態找環及 2-opt . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.4.3 動態找環 2-opt 篩選匹配演算法 . . . . . . . . . . . . . . . . . 24
2.5 實驗結果分析 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
2.5.1 匹配合併演算法匹配個數實驗 . . . . . . . . . . . . . . . . . . 27
2.5.2 動態找環 2-opt 匹配合併演算法匹配個數實驗 . . . . . . . . . 27
2.5.3 動態找環 2-opt 篩選匹配演算法匹配個數實驗 . . . . . . . . . 28
2.5.4 整體效能實驗 . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
第三章 應用 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.1 Travelling Salesman Problem . . . . . . . . . . . . . . . . . . . . . . . . 31
第四章 結論與未來展望 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.1 結論 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
4.2 未來展望 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
參考文獻 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
dc.language.isozh-TW
dc.subject近似比zh_TW
dc.subject啟發式演算法zh_TW
dc.subject最小權完美匹配zh_TW
dc.subjectminimum-weight perfect matchingen
dc.subjectheuristicen
dc.subjectapproximation ratioen
dc.title平面上的最小權完美匹配之啟發式演算法zh_TW
dc.titleHeuristics for the Minimum-Weight Perfect Matching Problem on a Planeen
dc.typeThesis
dc.date.schoolyear105-2
dc.description.degree碩士
dc.contributor.oralexamcommittee王釧茹(Chuan-Ju Wang),張經略(Ching-Lueh Chang)
dc.subject.keyword最小權完美匹配,啟發式演算法,近似比,zh_TW
dc.subject.keywordminimum-weight perfect matching,heuristic,approximation ratio,en
dc.relation.page38
dc.identifier.doi10.6342/NTU201703824
dc.rights.note有償授權
dc.date.accepted2017-08-20
dc.contributor.author-college電機資訊學院zh_TW
dc.contributor.author-dept資訊工程學研究所zh_TW
Appears in Collections:資訊工程學系

Files in This Item:
File SizeFormat 
ntu-106-1.pdf
  Restricted Access
668.26 kBAdobe PDF
Show simple item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved