61. The Traveling Salesman Problem I Session title. The traveling salesman problem I Mohammed Fazle Baki Pyramidal traveling salesman problem Tore Gruenert Implementing Ejection Chains http://dmawww.epfl.ch/roso.mosaic/ismp97/ismp_sess3_I050.html

Session title: The Traveling Salesman Problem I Session organizer: Santosh Narayan Kabadi Kabadi@unb.ca Abraham Punnen punnen@unbsj.ca Chair: Santosh Narayan Kabadi Session code: WE4-I-CM5 Room: Day and time: Wednesday, August 27 1997, 17:00 - 18:30 Speakers: Jack A.A. Van der Veen Sequencing with Job-Groups: Some Solvable Cases of the TSP Mohammed Fazle Baki Pyramidal Traveling Salesman Problem ... Implementing Ejection Chains for the TSP: Neighbourhoods and Evaluations

62. The Traveling Salesman Problem II Session title. The traveling salesman problem II Luis EN Gouveia The Assymetric Travelling Salesman Problem Aggregating a Multicommodity Flow into a http://dmawww.epfl.ch/roso.mosaic/ismp97/ismp_sess3_I490.html

Session title: The Traveling Salesman Problem II Chair: Yves W. Pochet Session code: TU1-I-IN202 Room: Day and time: Tuesday, August 26 1997, 08:15 - 09:45 Speakers: Osman Oguz An Extended Model for the Traveling Salesman Model: Some Polyhedral Results and Implications Luis E. N. Gouveia The Assymetric Travelling Salesman Problem: Aggregating a Multicommodity Flow into a Node Oriented Formulation

63. Traveling Salesman Problem traveling salesman problem. Given a set of cities, find the shortest route that visits each city exactly once and returns to the home city. http://www.rpi.edu/~mitchj/math1900/lp/node6.html

64. 01 Hostgold Hospedagem De Sites travelling salesman problem. algorithm, complexity (TSP or shortest path , Temas relacionados trash « Trash80 « traveling salesman problem http://www.hostgold.com.br/hospedagem-sites/o_que_e/travelling salesman problem

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65. Traveling Salesman Problem, Java Solution Finding a perfect solution for the NPcomplete problem of the traveling salesman is undoable. But finding an *excellent* route can be done in a few seconds, http://www.sum-it.nl/traveling_salesman.php3

Not Authorised SUMit has logged this error at 2005.09.17_02:09:58 for investigation. Possible cause Advice Your internet browser has been infected with spyware, used to create illegal copies of websites. Download SpyBot from safer-networking.org an use it to desinfect your PC. Use a browswer that has a better protection against unwelcome guests. Download Opera or FireFox Somebody has attempted to create an illegal copy of www.sum-it.nl from a computer at your company or ISP. Look somewhere else for information. SUMit security measures have detected a possible crime, a violation of Contact the SUMit helpdesk and describe: The URL of this page: /traveling_salesman.php3, your browser, and your operating system. Your email will help to solve the security problem. Thanks!

66. David Eppstein - Publications Traveling salesman and hamiltonian cycle problems Includes sections on the traveling salesman problem, Steiner trees, minimum weight triangulation, http://www.ics.uci.edu/~eppstein/pubs/tsp.html

David Eppstein - Publications Traveling salesman and hamiltonian cycle problems Worst-case bounds for subadditive geometric graphs M. Bern and D. Eppstein. 9th ACM Symp. Comp. Geom., San Diego, 1993, pp. 183-188. For many geometric graph problems for points in the unit square, such as minimum spanning trees matching , and traveling salesmen , the sum of edge lengths is O(sqrt n ) and the sum of d th powers of edge lengths is O(log n ). We provide a "gap theorem" showing that if these bounds do not hold for a class of graphs, both sums will instead be Omega( n ). For traveling salesmen the O(log n ) bound is tight but for some other graphs the sum of d th powers of edge lengths is O(1). BibTeX Citations Preprint of SCG version CiteSeer Approximation algorithms for geometric problems M. Bern and D. Eppstein. Approximation Algorithms for NP-hard Problems D. Hochbaum , ed., PWS Publishing, 1996, pp. 296-345. Considers problems for which no polynomial-time exact algorithms are known, and concentrates on bounds for worst-case approximation ratios, especially those depending intrinsically on geometry rather than on more general graph theoretic or metric space formulations. Includes sections on the traveling salesman problem , Steiner trees, minimum weight triangulation , clustering, and separation problems.

67. The Traveling Salesman Problem And Its Variations-Springer Discrete Mathematics This volume, which contains chapters written by reputable researchers, provides the state of the art in theory and algorithms for the traveling salesman http://www.springeronline.com/sgw/cda/frontpage/0,11855,5-10042-72-33637645-0,00

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68. Citations The Traveling Salesman Problem A Guided Tour Of EL Lawler, JK Lenstra, AHG Rinooy Kan, and DB Shmoys (eds.). The traveling salesman problem A guided tour of combinatorial optimization. http://citeseer.ist.psu.edu/context/81511/0

69. Citations Computer Solutions Of The Traveling Salesman Problem S. Lin., Computer solutions of the traveling salesman problem, Bell Systems Journal, vol. 44, pp. 22452269, 1965. http://citeseer.ist.psu.edu/context/2690/0

70. OPL Model Details: Traveling Salesman Problem The traveling salesman problem (TSP) is a classic problem in In the symmetric traveling salesman problem, the distances are the same in either direction http://www2.ilog.com/oplmodels/display.cfm?ID=41

71. Traveling Salesman Problem In the traveling salesman problem (TSP), N points (``cities ) are given, and every pair of cities i and j is separated by a distance http://cnls.lanl.gov/Highlights/1998-12/html/node3.html

72. IBM Technical Journals For fifty years the traveling salesman problem has fascinated mathematicians, computer scientists, and laymen. It is easily stated, but hard to solve; http://domino.research.ibm.com/tchjr/journalindex.nsf/0/236dbb33af6dd55185256bfa

73. GSRC Calibrating Achievable Design Bookshelf: Traveling Salesman Problem Slot MARCO GSRC Calibrating Achievable Design Bookshelf. traveling salesman problem Slot. Work in progress last updated Mon Dec 16 2002 http://vlsicad.eecs.umich.edu/BK/Slots/cache/vlsicad.ucsd.edu/GSRC/Bookshelf/Slo

MARCO GSRC Calibrating Achievable Design: Bookshelf Traveling Salesman Problem Slot Work in progress : last updated Mon Dec 16 2002 see other slots Ken Boese, Andrew B. Kahng Mike Oliver and Tim Walters Contents I. Introduction II. Data Formats III. Publicly available instances, solutions and reference performance results IV. Executable Utilities (converters, generators, statistics browsers, evaluators, constraint verifiers) V. Optimizers and other non-trivial executables VI. Common in-memory representations, parsers and other source codes I. Introduction This slot gives pointers to various TSP codes, benchmarks, and instance generators. II. Data Formats To come III. Publicly available instances, solutions and reference performance results TSPLIB DIMACS Benchmark Instances Bill Cook's TSP page IV. Executable Utilities To come V. Optimizers and non-trivial executables To come VI. Source codes DIMACS Benchmark Code and Instance Generation Codes Ken Boese's implementation of the Lin-Kernighan heuristic Keld Helsgaun's implementation of the Lin-Kernighan heuristic abk@ucsd.edu,oliver@cs.ucla.edu

74. NEAREST INSERTION TRAVELING SALESMAN PROBLEM By a reason similar to NEAREST MERGER traveling salesman problem, the nearest insertion heuristic does not specify a unique tour. However, the reduction is http://www.i.kyushu-u.ac.jp/~shoudai/P-complete/all/node57.html

75. NEAREST MERGER TRAVELING SALESMAN PROBLEM NEAREST MERGER traveling salesman problem. to an instance of NEAREST MERGER traveling salesman problem for which the nearest merger heuristic is unique. http://www.i.kyushu-u.ac.jp/~shoudai/P-complete/all/node56.html

76. ETH - ML Group - The Noisy Euclidean Traveling Salesman Problem And Learning We consider noisy Euclidean traveling salesman problems in the plane, which are random combinatorial problems with underlying structure. http://www.ml.inf.ethz.ch/publications/braun.mitpress02

News About us People Contact ... Help Search Research Education Publications Links ... Type of Publication The Noisy Euclidean Traveling Salesman Problem and Learning How to find us For travel information, click Mikio L. Braun and Joachim M. Buhmann In: Advances in Neural Information Processing, vol. 14, MIT Press, 2002. MIT Press Abstract We consider noisy Euclidean traveling salesman problems in the plane, which are random combinatorial problems with underlying structure. Gibbs sampling is used to compute average trajectories, which estimate the underlying structure common to all instances. This procedure requires identifying the exact relationship between permutations and tours. In a learning setting, the average trajectory is used as a model to construct solutions to new instances sampledfrom the same source. Experimental results show that the average trajectory can in fact estimate the underlying structure and that overfitting effects occur if the trajectory adapts too closely to a single instance. Download Publication as PDF Wichtiger Hinweis: folgender Seite Important Note: More information ETH Zurich Imprint May 24, 2005

77. The Traveling Salesman Problem The traveling salesman problem is a traditional computer science challenge. Its goal is to find the shortest circuit through a set of points. http://www.cs.arizona.edu/icon/oddsends/travels/travels.htm

The Traveling Salesman Problem The traveling salesman problem is a traditional computer science challenge. Its goal is to find the shortest circuit through a set of points. A common approach is to construct an initial path and then improve it incrementally through local optimizations. The travels.icn program illustrates several construction algorithms followed by application of the "2-opt" improvement algorithm; that algorithm deletes two segments at a time and reconnects their endpoints. If you look closely you may spot sections of a path that could be further improved by the "3-opt" algorithm which is not implemented here. Further Reading David S. Johnson. Local Optimization and the Traveling Salesman Problem. Springer-Verlag (1990), pp. 446-461. Icon home page

78. Traveling Salesman Problem The traveling salesman problem is to find the shortest circuitous path connecting N cities (meaning that a traveling salesman following that path would http://www.svengato.com/salesman.html

Traveling Salesman Problem (Simulated Annealing) The Traveling Salesman Problem is to find the shortest circuitous path connecting N cities (meaning that a traveling salesman following that path would visit each city only once). Although it can in principle be solved by brute force (by calculating the length of every possible circuit), this is not practical because the number of circuits grows so fast that even for N = 25 cities, it would take longer than the age of the universe (~10 billion years) to check every path, at a rate of one million paths per second! However, the method of simulated annealing quickly gives a reasonable answer, where "reasonable" means close enough to the true minimum path for practical purposes. Simulated annealing starts with the cities connected in a random order, and then considers making random changes in that order. If changing the order of cities leads to a shorter path, we accept that change. If the modification yields a longer path, we give ourselves a certain probability of accepting the modification less likely the larger the proposed increase in path length. We then gradually reduce this probability over time, in order to rule out shorter and shorter path increases thereby converging toward a path length close to the absolute minimum. The term "simulated annealing" comes from the analogy with annealing of metal, in which the metal is heated to a high temperature to give its atoms a lot of thermal motion, then is slowly cooled to give them a chance to align themselves into their lowest-energy (generally crystalline) configuration. Annealing makes the metal stronger than does rapid cooling (e.g. by plunging it into cold water), which would freeze the atoms wherever they happened to be, leaving microscopic cracks that make the metal brittle.

79. Travelling Salesman Problem (TSP) in G. Gutin and AP Punnen (Herausgeber), The traveling salesman problem and Its Variations, pp. 369 443, Kluwer Academic Publishers, Boston, 2002. http://www.intellektik.informatik.tu-darmstadt.de/~klausvpp/GAILS/node6.html

Quadratic Assignment Problem (QAP) Problemclasses Vorherige Seite: Problemclasses Travelling Salesman Problem (TSP) D AVID S. J OHNSON, L YLE A. M C G EOCH Experimental Analysis of Heuristics for the STSP in G. Gutin and A. P. Punnen (Herausgeber), The Traveling Salesman Problem and Its Variations, pp. 369 - 443, Kluwer Academic Publishers, Boston, 2002. [PDF] K ELD H ELSGAUN An effective implementation of the Lin-Kernighan traveling salesman heuristic in European Jorunal on Operations Research, Volume 126, Nummer 1, pp. 106 - 130, 2000. [PDF] Klaus Varrentrapp 2003-04-25

80. The Traveling Salesman Problem For those of you unfamiliar with the traveling salesman problem (TSP), 24441 The traveling salesman problem ~ serves an optimallength ambler. http://www.anagrammy.com/cgi-bin/displaymsg.pl?24434

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