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An Improved Particle Swarm Optimization Algorithm for the Travelling Salesman Problem

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Travelling Salesman Problem (TSP), which is a special case of Vehicle Routing Problem (VRP), is a very popular NP-Hard problem. Particle Swarm Optimization (PSO) is a recent development among approximate search algorithms which has significantly contributed in solving various continuous combinatorial optimization problems. Even though PSO has primarily been proposed for the continuous combinatorial problems, recent advancements of the PSO algorithm also successfully tackle various discrete optimization problems including TSP Though the PSO algorithm performs well to solve TSP problems, it considers different looking solutions which are basically the same solution with different appearance. So, some time consuming redundant processing may be done repeatedly. In this article, a novel solution structure is proposed to handle such redundant processing. Computational results have been compared to prior approaches for solving benchmark TSP problems which depicts better performance either in terms of obtaining expected results in reduced iterations or showing better cost trends to reach the optimal.
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Keywords: Fixed Starting; Particle Swarm Optimization; Travelling Salesman Problem

Document Type: Research Article

Affiliations: Department of Industrial and Management Engineering, Hankuk University of Foreign Studies, South Korea

Publication date: November 1, 2016

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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