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Particle Swarm Optimization with Partial Search to Solve Traveling Salesman Problem

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dc.contributor.advisor Akhand, Dr. Muhammad Aminul Haque
dc.contributor.author Akter, Shahina
dc.date.accessioned 2018-08-13T03:20:52Z
dc.date.available 2018-08-13T03:20:52Z
dc.date.copyright 2014
dc.date.issued 2014-02
dc.identifier.other ID 0907503
dc.identifier.uri http://hdl.handle.net/20.500.12228/347
dc.description This thesis is submitted to the Department of Computer Science and Engineering , Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, February 2014. en_US
dc.description Cataloged from PDF Version of Thesis.
dc.description Includes bibliographical references (pages 35-40).
dc.description.abstract The traveling salesman problem (TSP) is well-known combinatorial optimization problem. TSP requires to find the shortest circular tour visiting every city exactly once from a set of given cities. TSP is the most famous combinatorial problem and interest grows in recent years to solve it new ways. Almost every new approach for solving engineering and optimization problems has been tested on the TSP as a general test bench. Recently nature inspired population based methods including PSO has drawn great attraction to solve TSP. in this thesis introduce a Particle Swarm Optimization (PSO) base algorithm to solve TSP in different way which is defined as Velocity Tentative Particle Swarm Optimization (VTPSO). Existing method introduced the idea of Swap Operator (SO) and Swap Sequence (SS) in PSO to handle TSP. In TSP, each particle represents a complete tour and velocity is measured as a SS consisting with several SOs. A SO indicates two positions in the tour that might be swapped. In the existing method, a new tour is considered after applying a complete SS with all its SOs. Whereas, every SO implantation on a particle (i.e., a solution or a tour) gives a new solution and there might be a chance to get a better tour with some of SOs instead of all the SOs. The objective of the study is to achieve better result introducing using such partial search option for solving TSP. The proposed Velocity Tentative Particle Swarm Optimization (VTPSO) algorithm is shown to produce optimal solution within a less number of generations than Self-Tentative PSO (STPSO) and Swap Sequence based PSO (SSPSO) in solving several benchmark TSP problem en_US
dc.description.statementofresponsibility Shahina Akter
dc.format.extent 41 pages
dc.language.iso en_US en_US
dc.publisher Khulna University of Engineering & Technology (KUET), Khulna, Bangladesh. en_US
dc.rights without written permission. Khulna University of Engineering & Technology (KUET) thesis/ dissertation/internship reports are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited
dc.subject Particle Swarm Optimization (PSO) en_US
dc.subject Traveling Salesman Problem (TSP) en_US
dc.subject Swap Sequence (SS) en_US
dc.title Particle Swarm Optimization with Partial Search to Solve Traveling Salesman Problem en_US
dc.type Thesis en_US
dc.description.degree Master of Science in Computer Science and Engineering
dc.contributor.department Department of Computer Science and Engineering


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