Markov chain monte carlo and the traveling salesman problem.

by Liang Fa Ming. === Publication date from spine. === Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. === Includes bibliographical references (leaves 49-53). === ABSTRACT --- p.1 === Chapter CHAPTER 1 : --- Introduction --- p.2 === Chapter 1.1 : --- The TSP Problem --- p.2 === Chapter 1...

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Other Authors: Liang, F. (Faming) , 1970-
Format: Others
Language:English
Published: Chinese University of Hong Kong [199
Subjects:
Online Access:http://library.cuhk.edu.hk/record=b5888984
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spelling ndltd-cuhk.edu.hk-oai-cuhk-dr-cuhk_3214982019-02-19T03:56:32Z Markov chain monte carlo and the traveling salesman problem. Markov processes Monte Carlo method Traveling salesman problem by Liang Fa Ming. Publication date from spine. Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. Includes bibliographical references (leaves 49-53). ABSTRACT --- p.1 Chapter CHAPTER 1 : --- Introduction --- p.2 Chapter 1.1 : --- The TSP Problem --- p.2 Chapter 1.2: --- Application --- p.3 Chapter CHAPTER 2 : --- Review of Exact and Approximate Algorithms for TSP --- p.4 Chapter 2.1 : --- Exact Algorithm --- p.4 Chapter 2.2 : --- Heuristic Algorithms --- p.8 Chapter CHAPTER 3 : --- Markov Chain Monte Carlo Methods --- p.16 Chapter 3.1: --- Markov Chain Monte Carlo --- p.16 Chapter 3.2 : --- Conditioning and Gibbs Sampler --- p.17 Chapter 3.3: --- The Metropolis-Hasting Algorithm --- p.18 Chapter 3.4: --- Auxiliary Variable Methods --- p.21 Chapter CHAPTER 4: --- Weighted Markov Chain Monte Carlo Method --- p.24 Chapter CHAPTER 5 : --- Traveling Salesman Problem --- p.31 Chapter 5.1: --- Buildup Order --- p.33 Chapter 5.2: --- Path Construction through a Group of Points --- p.34 Chapter 5.3: --- Solving TSP Using the Weighted Markov Chain Method --- p.38 Chapter 5.4: --- Temperature Scheme --- p.40 Chapter 5.5 : --- How to Adjust the Constant Prior-Ratio --- p.41 Chapter 5.6: --- Validation of Our Algorithm by a Simple Example --- p.41 Chapter 5.7 : --- Adding/Deleting Blockwise --- p.42 Chapter 5.8: --- The sequential Optimal Method and Post Optimization --- p.43 Chapter 5. 9 : --- Composite Algorithm --- p.44 Chapter 5.10: --- Numerical Comparisons and Tests --- p.45 Chapter CHAPTER 6 : --- Conclusion --- p.48 REFERENCES --- p.49 APPENDIX A --- p.54 APPENDIX B --- p.58 APPENDIX C --- p.61 Chinese University of Hong Kong Liang, F. (Faming) , 1970- Chinese University of Hong Kong Graduate School. Division of Statistics. [1996] 1996 Text bibliography print 65 leaves : ill. ; 30 cm. cuhk:321498 http://library.cuhk.edu.hk/record=b5888984 eng Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) http://repository.lib.cuhk.edu.hk/en/islandora/object/cuhk%3A321498/datastream/TN/view/Markov%20chain%20monte%20carlo%20and%20the%20traveling%20salesman%20problem.jpghttp://repository.lib.cuhk.edu.hk/en/item/cuhk-321498
collection NDLTD
language English
format Others
sources NDLTD
topic Markov processes
Monte Carlo method
Traveling salesman problem
spellingShingle Markov processes
Monte Carlo method
Traveling salesman problem
Markov chain monte carlo and the traveling salesman problem.
description by Liang Fa Ming. === Publication date from spine. === Thesis (M.Phil.)--Chinese University of Hong Kong, 1995. === Includes bibliographical references (leaves 49-53). === ABSTRACT --- p.1 === Chapter CHAPTER 1 : --- Introduction --- p.2 === Chapter 1.1 : --- The TSP Problem --- p.2 === Chapter 1.2: --- Application --- p.3 === Chapter CHAPTER 2 : --- Review of Exact and Approximate Algorithms for TSP --- p.4 === Chapter 2.1 : --- Exact Algorithm --- p.4 === Chapter 2.2 : --- Heuristic Algorithms --- p.8 === Chapter CHAPTER 3 : --- Markov Chain Monte Carlo Methods --- p.16 === Chapter 3.1: --- Markov Chain Monte Carlo --- p.16 === Chapter 3.2 : --- Conditioning and Gibbs Sampler --- p.17 === Chapter 3.3: --- The Metropolis-Hasting Algorithm --- p.18 === Chapter 3.4: --- Auxiliary Variable Methods --- p.21 === Chapter CHAPTER 4: --- Weighted Markov Chain Monte Carlo Method --- p.24 === Chapter CHAPTER 5 : --- Traveling Salesman Problem --- p.31 === Chapter 5.1: --- Buildup Order --- p.33 === Chapter 5.2: --- Path Construction through a Group of Points --- p.34 === Chapter 5.3: --- Solving TSP Using the Weighted Markov Chain Method --- p.38 === Chapter 5.4: --- Temperature Scheme --- p.40 === Chapter 5.5 : --- How to Adjust the Constant Prior-Ratio --- p.41 === Chapter 5.6: --- Validation of Our Algorithm by a Simple Example --- p.41 === Chapter 5.7 : --- Adding/Deleting Blockwise --- p.42 === Chapter 5.8: --- The sequential Optimal Method and Post Optimization --- p.43 === Chapter 5. 9 : --- Composite Algorithm --- p.44 === Chapter 5.10: --- Numerical Comparisons and Tests --- p.45 === Chapter CHAPTER 6 : --- Conclusion --- p.48 === REFERENCES --- p.49 === APPENDIX A --- p.54 === APPENDIX B --- p.58 === APPENDIX C --- p.61
author2 Liang, F. (Faming) , 1970-
author_facet Liang, F. (Faming) , 1970-
title Markov chain monte carlo and the traveling salesman problem.
title_short Markov chain monte carlo and the traveling salesman problem.
title_full Markov chain monte carlo and the traveling salesman problem.
title_fullStr Markov chain monte carlo and the traveling salesman problem.
title_full_unstemmed Markov chain monte carlo and the traveling salesman problem.
title_sort markov chain monte carlo and the traveling salesman problem.
publisher Chinese University of Hong Kong
publishDate [199
url http://library.cuhk.edu.hk/record=b5888984
http://repository.lib.cuhk.edu.hk/en/item/cuhk-321498
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