Academic literature on the topic 'Application of travelling salesman problem'

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Journal articles on the topic "Application of travelling salesman problem"

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Damithabandara. "An Application to the Travelling Salesman Problem." Operations Research and Applications : An International Journal 4, no. 3/4 (November 30, 2017): 09–20. http://dx.doi.org/10.5121/oraj.2017.4402.

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Massinanke, Sambourou, and Chao Zhu Zhang. "Application of Genetic Algorithm on Travelling Salesman Person." Advanced Materials Research 1048 (October 2014): 526–30. http://dx.doi.org/10.4028/www.scientific.net/amr.1048.526.

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GA (Genetic algorithm) is an optimization method based on operators (mutation and crossover) utilizing a survival of the fittest idea. They are utilized favorably in various problems. (TSP) Travelling salesman problem is one of the famous studied. TSP is a permutation problem in which the aim is to determine the shortest tour between n different points (cities), otherwise, the problem aims to find a route covering all cities where that the total distance is minimal. In this study a single salesman travels to each of the cities and close the loop by returning to the city he started, the aim of this study is to determine the minimum number of generations in which salesman does the minimum path, cities are chosen at random as initial population. The new generations are then created iteratively till the proper path is attained.
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Singamsetty, Purusotham, and Jayanth Kumar Thenepalle. "An efficient genetic algorithm for solving open multiple travelling salesman problem with load balancing constraint." Decision Science Letters 10, no. 4 (2021): 525–34. http://dx.doi.org/10.5267/j.dsl.2021.5.003.

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The multiple travelling salesman problem (MTSP) is one of the widely studied combinatorial optimization problems with various theoretical and practical applications. However, most of the studies intended to deal with classical MTSP, very limited attention has been given to an open multiple travelling salesman problem and its variants. In this paper, an open multiple travelling salesman problem with load balancing constraint (OMTSPLB) is addressed. The OMTSPLB differs from the conventional MTSP, in which all the salesmen start from the central depot and need not come back to it after visiting the given number of cities by accomplishing the load balance constraint, which helps in fairly distributing the task among all salesmen. The problem aims to minimize the overall traversal distance/cost for operating open tours subject to the load balancing constraint. A zero-one integer linear programming (0-1 ILP) model and an efficient metaheuristic genetic algorithm (GA), is established for the OMTSPLB. Since no existing study on OMTSPLB, the proposed GA is tested on the relaxed version of the present model, comparative results are reported. The comparative results show that the proposed GA is competent over the existing algorithms. Furthermore, extensive experiments are carried out on OMTSPLB and the results show that proposed GA can find the global solution effectively.
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Derya, Tusan, Esra Dinler, and Barış Keçeci. "Selective generalized travelling salesman problem." Mathematical and Computer Modelling of Dynamical Systems 26, no. 1 (January 2, 2020): 80–118. http://dx.doi.org/10.1080/13873954.2019.1705496.

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Pham, Tu-San, Pieter Leyman, and Patrick De Causmaecker. "The intermittent travelling salesman problem." International Transactions in Operational Research 27, no. 1 (October 30, 2018): 525–48. http://dx.doi.org/10.1111/itor.12609.

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CHAN, DONALD, and DANIEL MERCIER. "IC insertion: an application of the travelling salesman problem." International Journal of Production Research 27, no. 10 (October 1989): 1837–41. http://dx.doi.org/10.1080/00207548908942657.

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Charon, Irène, and Olivier Hudry. "Application of the noising method to the travelling salesman problem." European Journal of Operational Research 125, no. 2 (September 2000): 266–77. http://dx.doi.org/10.1016/s0377-2217(99)00457-9.

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Laporte, Gilbert, Ardavan Asef-Vaziri, and Chelliah Sriskandarajah. "Some Applications of the Generalized Travelling Salesman Problem." Journal of the Operational Research Society 47, no. 12 (December 1996): 1461. http://dx.doi.org/10.2307/3010604.

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Laporte, Gilbert, Ardavan Asef-Vaziri, and Chelliah Sriskandarajah. "Some Applications of the Generalized Travelling Salesman Problem." Journal of the Operational Research Society 47, no. 12 (December 1996): 1461–67. http://dx.doi.org/10.1057/jors.1996.190.

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Laporte, G., and U. Palekar. "Some applications of the clustered travelling salesman problem." Journal of the Operational Research Society 53, no. 9 (September 2002): 972–76. http://dx.doi.org/10.1057/palgrave.jors.2601420.

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Dissertations / Theses on the topic "Application of travelling salesman problem"

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Haghighi, Maryam. "Application of Combinatorial Optimization Techniques in Genomic Median Problems." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20484.

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Constructing the genomic median of several given genomes is crucial in developing evolutionary trees, since the genomic median provides an estimate for the ordering of the genes in a common ancestor of the given genomes. This is due to the fact that the content of DNA molecules is often similar, but the difference is mainly in the order in which the genes appear in various genomes. The mutations that affect this ordering are called genome rearrangements, and many structural differences between genomes can be studied using genome rearrangements. In this thesis our main focus is on applying combinatorial optimization techniques to genomic median problems, with particular emphasis on the breakpoint distance as a measure of the difference between two genomes. We will study different variations of the breakpoint median problem from signed to unsigned, unichromosomal to multichromosomal, and linear to circular to mixed. We show how these median problems can be formulated in terms of problems in combinatorial optimization, and take advantage of well-known combinatorial optimization techniques and apply these powerful methods to study various median problems. Some of these median problems are polynomial and many are NP-hard. We find efficient algorithms and approximation methods for median problems based on well-known combinatorial optimization structures. The focus is on algorithmic and combinatorial aspects of genomic medians, and how they can be utilized to obtain optimal median solutions.
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Pogiatzis, Thomas. "Application of mixed-integer programming in chemical engineering." Thesis, University of Cambridge, 2013. https://www.repository.cam.ac.uk/handle/1810/245023.

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Mixed-Integer Programming has been a vital tool for the chemical engineer in the recent decades and is employed extensively in process design and control. This dissertation presents some new Mixed-Integer Programming formulations developed for two well-studied problems, one with a central role in the area of Optimisation, the other of great interest to the chemical industry. These are the Travelling Salesman Problem and the problem of scheduling cleaning actions for heat exchanger networks subject to fouling. The Travelling Salesman Problem finds a plethora of applications in many scientific disciplines, Chemical Engineering included. None of the mathematical programming formulations proposed for solving the problem considers fewer than O(n^2) binary degrees of freedom. The first part of this dissertation introduces a novel mathematical description of the Travelling Salesman Problem that succeeds in reducing the binary degrees of freedom to O(nlog2(n)). Three Mixed-Integer Linear Programming formulations are developed and the computational performance of these is tested through computational studies. Sophisticated methods are now available for scheduling the cleaning actions for networks of heat exchangers subject to fouling. In the majority of these, only one form of cleaning is used, which restores the performance of the exchanger back to its clean level. A recent study revised the scheduling problem for the case where there are several cleaning methods available. The second part of this dissertation extends their approach, developed for individual units, to heat exchanger networks and explores the concept of selection of cleaning techniques further. Mixed-Integer Programming formulations are proposed for the scheduling task, for two fouling scenarios: (i) chemical reaction fouling and (ii) biological fouling. A series of results are presented for the implementation of the scheduling formulations to networks of different sizes.
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Fu, Yao. "Applications of Circulations and Removable Pairings to TSP and 2ECSS." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31078.

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In this thesis we focus on two NP-hard and intensively studied problems: The travelling salesman problem (TSP), which aims to find a minimum cost tour that visits every node exactly once in a complete weighted graph, and the 2-edge-connected spanning subgraph problem (2ECSS), which aims to find a minimum size 2-edge-connected spanning subgraph in a given graph. TSP and 2ECSS have many real world applications. However, both problems are NP-hard which means it is unlikely that polynomial time algorithms exist to solve them, so methods that return close to optimal solutions are sought. In this thesis we mainly focus on k-approximation algorithms for the two problems, which efficiently return a solution within k times of the optimal solution. For a special case of TSP called graph TSP, using ideas from Momke and Svensson, we present a 25/18-approximation algorithm for a special class of graphs using circulations and T-joins, which improves the previous known best bound of 7/5 for such graphs. Moreover, if the graph does not contain special nodes, our algorithm ensures the ratio of 4/3. For 2ECSS, given any k-edge-connected graph G=(V,E), |V|=n, |E|=m, we present an approximation algorithm that gives a 2-edge-connected spanning subgraph with the number of edges at most n+(m-n)/(k-1)-(k-2)/(k-1) with a novel use of circulations, which improves both the approximation ratio and the simplicity of the proof compared to a result by Huh in 2004.
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Mitchell, Sophia. "A Cascading Fuzzy Logic Approach for Decision Making in Dynamic Applications." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1448037866.

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Butler, Martin. "2-period travelling salesman problem." Thesis, University of Southampton, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.242250.

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Gupta, Anil Kumar. "On a generalized travelling salesman problem." Thesis, University of Ottawa (Canada), 1986. http://hdl.handle.net/10393/4745.

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Bryant, Kylie. "Genetic Algorithms and the Travelling Salesman Problem." Scholarship @ Claremont, 2000. https://scholarship.claremont.edu/hmc_theses/126.

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Genetic algorithms are an evolutionary technique that use crossover and mutation operators to solve optimization problems using a survival of the fittest idea. They have been used successfully in a variety of different problems, including the traveling salesman problem. In the traveling salesman problem we wish to find a tour of all nodes in a weighted graph so that the total weight is minimized. The traveling salesman problem is NP-hard but has many real world applications so a good solution would be useful. Many different crossover and mutation operators have been devised for the traveling salesman problem and each give different results. We compare these results and find that operators that use heuristic information or a matrix representation of the graph give the best results.
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Ahrens, Barry. "A Tour Construction Framework for the Travelling Salesman Problem." NSUWorks, 2012. http://nsuworks.nova.edu/gscis_etd/74.

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The Tour Construction Framework (TCF) integrates both global and local heuristics in a complementary framework in order to efficiently solve the Travelling Salesman Problem (TSP). Most tour construction heuristics are strictly local in nature. However, the experimental method presented in this research includes a global heuristic to efficiently solve the TSP. The Global Path (GP) component and Super Node (SN) component comprise the TCF. Each component heuristic is tuned with one or more parameters. Genetic Algorithms (GA) are used to train the collection of parameters for the TCF components on subsets of benchmark TSPs. The GA results are used to run the TCF on the full TSP instances. The performance of the TCF is evaluated for speed, accuracy, and computational complexity, and it is compared against six mainstream TSP solvers: Lin-Kernighan-Helsgaun (LKH-2), 2-Opt, Greedy, Boruvka, Quick-Boruvka, and Nearest Neighbor. The empirical study demonstrates the effectiveness of the TCF in achieving near-optimal solutions for the TSP with reasonable costs.
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Schmitting, Walter. "Das Traveling-Salesman-Problem Anwendungen und heuristische Nutzung von Voronoi-Delaunay-Strukturen zur Lösung euklidischer, zweidimensionaler Traveling-Salesman-Probleme /." Münster : Schmitting, 2000. http://deposit.ddb.de/cgi-bin/dokserv?idn=960608176.

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Krishnamoorthy, Mohan. "Contributions to the solution of the symmetric travelling salesman problem." Thesis, Imperial College London, 1991. http://hdl.handle.net/10044/1/46875.

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Books on the topic "Application of travelling salesman problem"

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Farhat, Idriss. Evaluation of shortest path algorithms for an application of the travelling salesman problem. Oxford: Oxford Brookes University, 2004.

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Green, D. R. The travelling salesman problem. Loughborough: Department of Mathematical Sciences, Loughborough University of Technology, 1991.

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Gutin, Gregory. The Travelling Salesman Problem and Its Variations. Dordrecht: Springer, 2002.

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Dr, Dimitrijević Vladimir, and Milosavljević Milan, eds. Variations on the travelling salesman theme. Beograd: Libra Produkt, 1996.

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Claus, A. An arc flow formulation for the travelling salesman problem. Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology, 1987.

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Mtenzi, Frederick Japhet. Experimental design methodology for large, symmetric, sparse, Travelling Salesman Problem. Dublin: University College Dublin, Dept of Management Information Systems, 1997.

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Brendel, Thomas. Dialoggestützte Tourenplanung unter besonderer Berücksichtigung von Belieferungszeitintervallen. Frankfurt am Main: P. Lang, 1987.

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Perttunen, Jukka. Computational experiments on edge exchange heuristics for the Euclidean travelling salesman problem. Vaasa: Universitatis Wasaensis, 1993.

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Fox, Colin Andrew. A very first encounter with simulated annealing with particular reference to the travelling salesman problem. Salford: University of Salford, 1991.

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Dyte, Peter W. A study of the heuristic solution to the travelling salesman problem. 1985.

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Book chapters on the topic "Application of travelling salesman problem"

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Perez, Diego, Philipp Rohlfshagen, and Simon M. Lucas. "Monte-Carlo Tree Search for the Physical Travelling Salesman Problem." In Applications of Evolutionary Computation, 255–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29178-4_26.

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Martínez, Ana Priscila, and Lidia Marina López. "Heuristic Variant for the Travelling Salesman Problem. Application Case: Sports Fishing Circuit." In Communications in Computer and Information Science, 235–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-20787-8_17.

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Mérida-Casermeiro, E., J. Muñoz-Pérez, and E. Domínguez-Merino. "An N-Parallel Multivalued Network: Applications to the Travelling Salesman Problem." In Computational Methods in Neural Modeling, 406–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44868-3_52.

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Sourabh Joshi and Sarabjit Kaur. "Ant Colony Optimization Meta-heuristic for Solving Real Travelling Salesman Problem." In Emerging Research in Computing, Information, Communication and Applications, 55–63. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0287-8_5.

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Hashim, Zakiah, and Wan Rosmanira Ismail. "Applications of Travelling Salesman Problem in Optimizing Tourist Destinations Visit in Langkawi." In Regional Conference on Science, Technology and Social Sciences (RCSTSS 2014), 265–73. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0534-3_25.

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Tuani, Ahamed Fayeez, Edward Keedwell, and Matthew Collett. "H-ACO: A Heterogeneous Ant Colony Optimisation Approach with Application to the Travelling Salesman Problem." In Lecture Notes in Computer Science, 144–61. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78133-4_11.

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Jędrzejowicz, Piotr, and Izabela Wierzbowska. "Parallel Cooperating A-Teams Solving Instances of the Euclidean Planar Travelling Salesman Problem." In Agent and Multi-Agent Systems: Technologies and Applications, 456–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-22000-5_47.

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Chaudhari, Kinjal, and Ankit Thakkar. "Travelling Salesman Problem: An Empirical Comparison Between ACO, PSO, ABC, FA and GA." In Emerging Research in Computing, Information, Communication and Applications, 397–405. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6001-5_32.

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Urquhart, Neil, Cathy Scott, and Emma Hart. "Using an Evolutionary Algorithm to Discover Low CO2 Tours within a Travelling Salesman Problem." In Applications of Evolutionary Computation, 421–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12242-2_43.

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Oliinyk, Andrii, Ievgen Fedorchenko, Alexander Stepanenko, Mykyta Rud, and Dmytro Goncharenko. "Implementation of Evolutionary Methods of Solving the Travelling Salesman Problem in a Robotic Warehouse." In Data-Centric Business and Applications, 263–92. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-43070-2_13.

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Conference papers on the topic "Application of travelling salesman problem"

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Assaf, Mustafa, and Malick Ndiaye. "Multi travelling salesman problem formulation." In 2017 4th International Conference on Industrial Engineering and Applications (ICIEA). IEEE, 2017. http://dx.doi.org/10.1109/iea.2017.7939224.

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Goyal, Nitesh. "Grading a Microcontroller: A Travelling Salesman Problem Application." In 2006 International Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/icece.2006.355636.

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Syambas, Nana Rahmana, Shasa Salsabila, and Galura Muhammad Suranegara. "Fast heuristic algorithm for travelling salesman problem." In 2017 11th International Conference on Telecommunication Systems Services and Applications (TSSA). IEEE, 2017. http://dx.doi.org/10.1109/tssa.2017.8272945.

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Palhares, R. A., and M. C. B. AraUjo. "Vehicle Routing: Application of Travelling Salesman Problem in a Dairy." In 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2018. http://dx.doi.org/10.1109/ieem.2018.8607472.

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Patra, Chiranjib, and Pratyush. "Vector ANT Colony Optimization and Travelling Salesman Problem." In Fourth International Conference on Computer Science, Engineering and Applications. Academy & Industry Research Collaboration Center (AIRCC), 2014. http://dx.doi.org/10.5121/csit.2014.4711.

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Leelavathy, T., and K. Ganesan. "A distinct technique for fuzzy travelling salesman problem." In THE 11TH NATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5112300.

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Grabusts, Peter, and Jurijs Musatovs. "The Application of Simulated Annealing Method for Solving Travelling Salesman Problem." In The 4th Global Virtual Conference. Publishing Society, 2016. http://dx.doi.org/10.18638/gv.2016.4.1.732.

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Erol, Mehmet Hamza, and Faruk Bulut. "Real-time application of travelling salesman problem using Google Maps API." In 2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT). IEEE, 2017. http://dx.doi.org/10.1109/ebbt.2017.7956764.

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Agrawal, Mayank, and Vinod Jain. "Applying Improved Genetic Algorithm to Solve Travelling Salesman Problem." In 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). IEEE, 2020. http://dx.doi.org/10.1109/icirca48905.2020.9182884.

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Karthy, T., and S. Priyanka. "Comparative analysis of the optimal solutions of travelling salesman problem." In THE 11TH NATIONAL CONFERENCE ON MATHEMATICAL TECHNIQUES AND APPLICATIONS. AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5112215.

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Reports on the topic "Application of travelling salesman problem"

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Fogel, David B. Addressing the Travelling Salesman Problem through Evolutionary Adaptation. Fort Belvoir, VA: Defense Technical Information Center, January 1987. http://dx.doi.org/10.21236/ada179992.

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