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Academic literature on the topic 'TSP'

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Published: 4 June 2021

Last updated: 11 March 2023

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Journal articles on the topic "TSP"

Tzvetkov, Petre, Xifeng Yan, and Jiawei Han. "TSP: Mining top-k closed sequential patterns." Knowledge and Information Systems 7, no. 4 (May 2005): 438–57. http://dx.doi.org/10.1007/s10115-004-0175-4.

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Farbstein, Boaz, and Asaf Levin. "Deadline TSP." Theoretical Computer Science 771 (June 2019): 83–92. http://dx.doi.org/10.1016/j.tcs.2018.11.016.

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Armon, Amitai, Adi Avidor, and Oded Schwartz. "Cooperative TSP." Theoretical Computer Science 411, no. 31-33 (June 2010): 2847–63. http://dx.doi.org/10.1016/j.tcs.2010.04.016.

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Chaourar, Brahim. "The Kth TSP is pseudopolynomial when TSP is polynomial." Discrete Mathematics, Algorithms and Applications 10, no. 05 (October 2018): 1850058. http://dx.doi.org/10.1142/s1793830918500581.

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Given an undirected graph [Formula: see text] with a weight function [Formula: see text], and a positive integer [Formula: see text], the Kth Traveling Salesman Problem (Kth TSP) is to find [Formula: see text] Hamilton cycles [Formula: see text] such that, for any Hamilton cycle [Formula: see text], we have [Formula: see text]. This problem is NP-hard even for [Formula: see text] fixed. We prove that Kth TSP is pseudopolynomial when TSP is polynomial.

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Barlow, David, and David M. Lilien. "Micro TSP 7.0." Economic Journal 102, no. 410 (January 1992): 191. http://dx.doi.org/10.2307/2234878.

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Pesch, Erwin, and Fred Glover. "TSP ejection chains." Discrete Applied Mathematics 76, no. 1-3 (June 1997): 165–81. http://dx.doi.org/10.1016/s0166-218x(96)00123-0.

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Farbstein, Boaz, and Asaf Levin. "Discounted Reward TSP." Algorithmica 80, no. 2 (December 12, 2016): 472–95. http://dx.doi.org/10.1007/s00453-016-0264-2.

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Martens, Rainer. "TSP Publisher Statement." Sport Psychologist 1, no. 1 (March 1987): 1. http://dx.doi.org/10.1123/tsp.1.1.1.

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Shi, X. H., Y. C. Liang, H. P. Lee, C. Lu, and Q. X. Wang. "Particle swarm optimization-based algorithms for TSP and generalized TSP." Information Processing Letters 103, no. 5 (August 2007): 169–76. http://dx.doi.org/10.1016/j.ipl.2007.03.010.

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Hwang, Sook-Hi, Il-Yong Weon, Sung-Bum Ko, and Chang-Hoon Lee. "S-MINE Algorithm for the TSP." KIPS Transactions:PartB 18B, no. 2 (April 30, 2011): 73–82. http://dx.doi.org/10.3745/kipstb.2011.18b.2.073.

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Dissertations / Theses on the topic "TSP"

Desjardins, Nicholas. "On Applying Methods for Graph-TSP to Metric TSP." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35613.

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The Metric Travelling Salesman Problem, henceforth metric TSP, is a fundamental problem in combinatorial optimization which consists of finding a minimum cost Hamiltonian cycle (also called a TSP tour) in a weighted complete graph in which the costs are metric. Metric TSP is known to belong to a class of problems called NP-hard even in the special case of graph-TSP, where the metric costs are based on a given graph. Thus, it is highly unlikely that efficient methods exist for solving large instances of these problems exactly. In this thesis, we develop a new heuristic for metric TSP based on extending ideas successfully used by Mömke and Svensson for the special case of graph-TSP to the more general case of metric TSP. We demonstrate the efficiency and usefulness of our heuristic through empirical testing. Additionally, we turn our attention to graph-TSP. For this special case of metric TSP, there has been much recent progress with regards to improvements on the cost of the solutions. We find the exact value of the ratio between the cost of the optimal TSP tour and the cost of the optimal subtour linear programming relaxation for small instances of graph-TSP, which was previously unknown. We also provide a simplified algorithm for special graph-TSP instances based on the subtour linear programming relaxation.

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Feng, Yinda. "Ant colony for TSP." Thesis, Högskolan Dalarna, Datateknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4824.

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The aim of this work is to investigate Ant Colony Algorithm for the traveling salesman problem (TSP). Ants of the artificial colony are able to generate successively shorter feasible tours by using information accumulated in the form of a pheromone trail deposited on the edges of the TSP graph. This paper is based on the ideas of ant colony algorithm and analysis the main parameters of the ant colony algorithm. Experimental results for solving TSP problems with ant colony algorithm show great effectiveness.

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Maris, Frederic. "Planification SAT et Planification Temporellement Expressive. Les Systèmes TSP et TLP-GP." Phd thesis, Université Paul Sabatier - Toulouse III, 2009. http://tel.archives-ouvertes.fr/tel-00442014.

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Maris, Frédéric. "Planification SAT et planification temporellement expressive : les systèmes TSP et TLP-GP." Toulouse 3, 2009. http://thesesups.ups-tlse.fr/688/.

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Cette thèse s'inscrit dans le cadre de la planification de tâches en intelligence artificielle. Après avoir introduit le domaine et les principaux algorithmes de planification dans le cadre classique, nous présentons un état de l'art de la planification SAT. Nous analysons en détail cette approche qui permet de bénéficier directement des améliorations apportées régulièrement aux solveurs SAT. Nous proposons de nouveaux codages qui intègrent une stratégie de moindre engagement en retardant le plus possible l'ordonnancement des actions. Nous présentons ensuite le système TSP que nous avons implémenté pour comparer équitablement les différents codages puis nous détaillons les résultats de nombreux tests expérimentaux qui démontrent la supériorité de nos codages par rapport aux codages existants. Nous présentons ensuite un état de l'art de la planification temporelle en analysant les algorithmes et l'expressivité de leurs langages de représentation. La très grande majorité de ces planificateurs ne permet pas de résoudre des problèmes réels pour lesquels la concurrence des actions est nécessaire. Nous détaillons alors les deux approches originales de notre système TLP-GP permettant de résoudre ce type de problèmes. Ces approches sont comparables à la planification SAT, une grande partie du travail de recherche étant déléguée à un solveur SMT. Nous proposons ensuite des extensions du langage de planification PDDL qui permettent une certaine prise en compte de l'incertitude, du choix, ou des transitions continues. Nous montrons enfin, grâce à une étude expérimentale, que nos algorithmes permettent de résoudre des problèmes réels nécessitant de nombreuses actions concurrentes
This thesis deals with Artificial Intelligence planning. After introducing the domain and the main algorithms in the classical framework of planning, we present a state of the art of SAT planning. We analyse in detail this approach which allows us to benefit directly from improvements brought regularly to SAT solvers. We propose new encodings integrating a least-commitment strategy postponing as much as possible the scheduling of actions. We then introduce the TSP system which we have implemented to equitably compare the different encodings and we detail the results of numerous experimental tests which show the superiority of our encodings in comparison with the existing ones. We introduce then a state of the art of temporal planning by analysing algorithms and expressiveness of their representation languages. The great majority of these planners do not allow us to solve real problems for which the concurrency of actions is required. We then detail the two original approaches of our TLP-GP system which allow us to solve this type of problem. As with SAT planning, a large part of search work is delegated to a SMT solver. We then propose extensions of the PDDL planning language which allows us to a certain extent to take into account uncertainty, choice, or continuous transitions. We show finally, thanks to an experimental study, that our algorithms allow us to solve real problems requiring numerous concurrent actions

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Na, Byungsoo. "Heurisic approaches for no-depot k-traveling salesmen problem with a minmax objective." Texas A&M University, 2003. http://hdl.handle.net/1969.1/5825.

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This thesis deals with the no-depot minmax Multiple Traveling Salesmen Problem (MTSP), which can be formulated as follows. Given a set of n cities and k salesmen,find k disjoint tours (one for each salesmen) such that each city belongs to exactly one tour and the length of the longest of k tours is minimized. The no-depot assumption means that the salesmen do not start from and return to one fixed depot. The no-depot model can be applied in designing patrolling routes, as well as in business situations, especially where salesmen work from home or the company has no central office. This model can be also applied to the job scheduling problem with n jobs and k identical machines. Despite its potential applicability to a number of important situations, the research literature on the no-depot minmax k-TSP has been limited, with no reports on computational experiments. The previously published results included the proof of NP-hardness of the problem of interest, which motivates using heuristics for its solution. This thesis proposes several construction heuristic algorithms, including greedy algorithms, cluster first and route second algorithms, and route first and cluster second algorithms. As a local search method for a single tour, 2-opt search and Lin-Kernighan were used, and for a local search method between multiple tours, relocation and exchange (edge heuristics) were used. Furthermore, to prevent the drawback of trapping in the local minima, the simulated annealing method is used. Extensive computational experiments were carried out using TSPLIB instances. Among construction algorithms, route first and cluster second algorithms including removing two edges method performed best. In terms of running time, clustering first and routing second algorithms took shorter time on large-scale instances. The simulated annealing could produce better solutions than the descent method, but did not always perform well in terms of average solution. To evaluate the performance of the proposed heuristic methods, their solutions were compared with the optimal solutions obtained using a mixed-integer programming formulation of the problem. For small-scale problems, heuristic solutions were equal to the optimal solution output by CPLEX.

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Gavrilov, Andrej. "Komandinio programų kūrimo proceso tyrimas." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2009. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2008~D_20090908_201812-38601.

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Siekiant pagerinti kuriamų programinių produktų kokybę, IT įmonės taiko skirtingus proceso modelius. Populiariausi iš jų gebėjimo brandos modelis (CMMI) ir ISO 15504. Šie modeliai nusako, kas (kokie procesai) turi būti vykdoma brandžioje organizacijoje, tačiau neatsako į klausimą: kaip tai turi būti daroma. Komandinis programų kūrimo procesas (TSP) pateikia strategiją, kartu su procedūrų rinkiniu, skirtą disciplinuotų programų kūrimo metodų naudojimui komandos lygyje. Pagrindinė su TSP susijusi problema – oficialios dokumentacijos trūkumas. Pirmas darbo tikslas yra rekonstruoti TSP metodiką. Antras tikslas yra sukurti TSP diegimo metodiką. Pirmoje darbo dalyje yra aprašyta bendra TSP struktūra, TSP ryšys su asmeniniu programų kūrimo procesu (PSP) ir brandos modeliu CMMI. Antroje dalyje yra pateiktas rekonstruotas TSP modelis ir TSP diegimo metodika apibrėžtam projekto komandos tipui.
IT organizations use different models to guide their software process improvement efforts. The most popular are the Capability Maturity Model Integration for Software (CMMI-SW) and ISO 15504. Still these organizations often struggle with implementation details. Both the CMMI-SW and ISO 15504 describe what an organization at a high level of process maturity should be doing, but do not says how it should be implemented. The Team Software Process (TSP) provides a framework as well as a set of processes, procedures, guidelines, and tools for project teams to use in the mature software development process. The main problem of the Team Software Process is the lack of official documentation. So the first goal of this master thesis is to reconstruct TSP methodology. The second goal is to produce TSP implementation guide. This master thesis contains the main structure of the TSP, it’s relation with the Personal Software Process (PSP) ant the Capability Maturity Model (CMMI), reconstructed TSP model and TSP implementation guide for defined project team type.

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Palbom, Anna. "On Approximating Asymmetric TSP and Related Problems." Licentiate thesis, Stockholm : School of Computer Science and Communication, Kungl Tekniska högskolan, (KTH), 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3932.

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Hahsler, Michael, and Kurt Hornik. "TSP - Infrastructure for the Traveling Salesperson Problem." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2006. http://epub.wu.ac.at/1230/1/document.pdf.

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The traveling salesperson or salesman problem (TSP) is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Despite this simple problem statement, solving the TSP is difficult since it belongs to the class of NP-complete problems. The importance of the TSP arises besides from its theoretical appeal from the variety of its applications. In addition to vehicle routing, many other applications, e.g., computer wiring, cutting wallpaper, job sequencing or several data visualization techniques, require the solution of a TSP. In this paper we introduce the R package TSP which provides a basic infrastructure for handling and solving the traveling salesperson problem. The package features S3 classes for specifying a TSP and its (possibly optimal) solution as well as several heuristics to find good solutions. In addition, it provides an interface to Concorde, one of the best exact TSP solvers currently available. (author's abstract)
Series: Research Report Series / Department of Statistics and Mathematics

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Hahsler, Michael, and Kurt Hornik. "TSP - Infrastructure for the Traveling Salesperson Problem." American Statistical Association, 2007. http://epub.wu.ac.at/3990/1/TSP.pdf.

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The traveling salesperson (or, salesman) problem (TSP) is a well known and important combinatorial optimization problem. The goal is to find the shortest tour that visits each city in a given list exactly once and then returns to the starting city. Despite this simple problem statement, solving the TSP is difficult since it belongs to the class of NP-complete problems. The importance of the TSP arises besides from its theoretical appeal from the variety of its applications. Typical applications in operations research include vehicle routing, computer wiring, cutting wallpaper and job sequencing. The main application in statistics is combinatorial data analysis, e.g., reordering rows and columns of data matrices or identifying clusters. In this paper, we introduce the R package TSP which provides a basic infrastructure for handling and solving the traveling salesperson problem. The package features S3 classes for specifying a TSP and its (possibly optimal) solution as well as several heuristics to find good solutions. In addition, it provides an interface to Concorde, one of the best exact TSP solvers currently available. (authors' abstract)

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Zhang, Jun. "Conception et réalisation de l'interface Moduleco-TSP." Paris 9, 1990. https://portail.bu.dauphine.fr/fileviewer/index.php?doc=1990PA090035.

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Cette thèse a pour objectif de concevoir et de réaliser l'interface entre le logiciel Moduleco et le logiciel TSP. Les principaux sujets abordés sont les suivants: 1) études approfondies de Moduleco-logiciel de modélisation macro-économique, et de TSP-logiciel de statistique et de calcul économétrique; 2) génération automatique de programmes TSP; 3) traduction des équations de syntaxe Moduleco en équations de syntaxe TSP; 4) récupération des résultats TSP dans Moduleco. Ce travail a été réalisé au sein du projet Moduleco de l'Inria-Rocquencourt

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Books on the topic "TSP"

TSP Architects & Planners. TSP Architects & Planners. Singapore: The Authors, 1992.

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Humphrey, Watts S. TSP: Coaching development teams. Upper Saddle River, NJ: Addison-Wesley, 2006.

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Humphrey, Watts S. TSP--leading a development team. Upper Saddle River, NJ: Addison-Wesley, 2006.

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Pomiankowski, Nick. The TSP package on the ICL 2960. Portsmouth: Portsmouth Polytechnic, School of Information Science, 1986.

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The traveling salesman: Computational solutions for TSP applications. Berlin: Springer-Verlag, 1994.

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Mester, D. Discrete optimization for TSP-like genome mapping problems. New York: Nova Science Publishers, 2010.

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D, Mester, ed. Discrete optimization for TSP-like genome mapping problems. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Kyeryang kyŏngjehak pangbŏmnon: TSP rŭl iyonghan kʻŏmpʻyutʻŏ punsŏk kipŏp. [Seoul]: Pibong Chʻulpʻansa, 1989.

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Smith, Harriet R. Transit signal priority (TSP): A planning and implementation handbook. Washington, DC: ITS America, 2005.

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Instituto Nacional de Estadística, Geografía e Informática (Mexico), ed. Manual de análisis de paquete computacional TSP (Time Series Processor). México: Instituto Nacional de Estadística, Geografía e Informática, 1985.

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Book chapters on the topic "TSP"

Gass, Saul I., and Carl M. Harris. "TSP." In Encyclopedia of Operations Research and Management Science, 854. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_1076.

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Shekhar, Shashi, and Hui Xiong. "TSP." In Encyclopedia of GIS, 1181. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1417.

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Bläser, Markus. "Metric TSP." In Encyclopedia of Algorithms, 1276–79. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-2864-4_230.

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Bläser, Markus. "Metric TSP." In Encyclopedia of Algorithms, 517–19. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-30162-4_230.

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Farbstein, Boaz, and Asaf Levin. "Deadline TSP." In Approximation and Online Algorithms, 52–65. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89441-6_5.

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Armon, Amitai, Adi Avidor, and Oded Schwartz. "Cooperative TSP." In Lecture Notes in Computer Science, 40–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11841036_7.

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Vazirani, Vijay V. "Euclidean TSP." In Approximation Algorithms, 84–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-04565-7_11.

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Salajegheh, Ali. "Tsp-1." In Angiogenesis in Health, Disease and Malignancy, 345–50. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28140-7_55.

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Lodi, Andrea, and Abraham P. Punnen. "TSP Software." In Combinatorial Optimization, 737–49. Boston, MA: Springer US, 2007. http://dx.doi.org/10.1007/0-306-48213-4_16.

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Aprea, Mauro, Esteban Feuerstein, Gustavo Sadovoy, and Alejandro Strejilevich de Loma. "Discrete online TSP." In Algorithmic Aspects in Information and Management, 29–42. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02158-9_5.

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Conference papers on the topic "TSP"

Traub, Vera, Jens Vygen, and Rico Zenklusen. "Reducing path TSP to TSP." In STOC '20: 52nd Annual ACM SIGACT Symposium on Theory of Computing. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3357713.3384256.

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Abdulrazaq, Muhammad Bashir, Yusuf Suleiman Tahir, Suleiman Sha'aban, and Muhammed Sani Jibia. "Polynomial Reduction of TSP to Freely Open-loop TSP." In 2019 2nd International Conference of the IEEE Nigeria Computer Chapter (NigeriaComputConf). IEEE, 2019. http://dx.doi.org/10.1109/nigeriacomputconf45974.2019.8949664.

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"TSP 2020 Contents." In 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. http://dx.doi.org/10.1109/tsp49548.2020.9163407.

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"TSP 2020 Reviewers." In 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. http://dx.doi.org/10.1109/tsp49548.2020.9163429.

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"TSP 2020 Preface." In 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. http://dx.doi.org/10.1109/tsp49548.2020.9163514.

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"TSP 2019 Preface." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8768865.

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"TSP 2019 Reviewers." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8768855.

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"TSP 2019 TOC." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8769110.

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"TSP 2020 Author Index." In 2020 43rd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2020. http://dx.doi.org/10.1109/tsp49548.2020.9163527.

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"TSP 2019 Conference Information." In 2019 42nd International Conference on Telecommunications and Signal Processing (TSP). IEEE, 2019. http://dx.doi.org/10.1109/tsp.2019.8769116.

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Reports on the topic "TSP"

Nichols, William R., Alvaro Tasistro, Diego Vallespir, Joao P. Faria, Mushtaq Raza, Pedro Castro, Cesar Duarte, Elias Fallon, Lee Gazlay, and Shigeru Kusakabe. TSP Symposium 2012 Proceedings. Fort Belvoir, VA: Defense Technical Information Center, November 2012. http://dx.doi.org/10.21236/ada611067.

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Tamura, Shurei. Integrating CMMI and TSP/PSP: Using TSP Data to Create Process Performance Models. Fort Belvoir, VA: Defense Technical Information Center, November 2009. http://dx.doi.org/10.21236/ada512409.

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Humphrey, Watts S. The Team Software Process (TSP). Fort Belvoir, VA: Defense Technical Information Center, November 2000. http://dx.doi.org/10.21236/ada386941.

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Sasao, Shigeru, William Nichols, and James McCurley. Using TSP Data to Evaluate Your Project Performance. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada537112.

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Chick, Timothy A., Robert Cannon, James McHale, William Nichols, Marsha Pomeroy-Huff, Jefferson Welch, and Alan Willet. Team Software Process (TSP) Coach Mentoring Program Guidebook. Fort Belvoir, VA: Defense Technical Information Center, August 2009. http://dx.doi.org/10.21236/ada512361.

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Humphrey, Watts S., Timothy A. Chick, William Nichols, and Marsha Pomeroy-Huff. Team Software Process (TSP) Body of Knowledge (BOK). Fort Belvoir, VA: Defense Technical Information Center, July 2010. http://dx.doi.org/10.21236/ada634307.

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Robert Radtke. NEW HIGH STRENGTH AND FASTER DRILLING TSP DIAMOND CUTTERS. Office of Scientific and Technical Information (OSTI), January 2006. http://dx.doi.org/10.2172/894521.

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Lugar, R. M. Results of TSP metals monitoring at McMurdo Station, Antarctica. Office of Scientific and Technical Information (OSTI), April 1994. http://dx.doi.org/10.2172/10167037.

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Blanchet, M., and F. Parent. IPv6 Tunnel Broker with the Tunnel Setup Protocol (TSP). RFC Editor, February 2010. http://dx.doi.org/10.17487/rfc5572.

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Whitley, L. D., and Adele E. Howe. Exploiting Elementary Landscapes for TSP, Vehicle Routing and Scheduling. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ada622665.

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