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An Approach for Solving Traveling Salesman Problem using Hybrid Ant Colony Optimization

http://hdl.handle.net/20.500.12678/0000004971
9eb52d35-fc24-4f0b-94c0-6ae37c5af9b9
44568bb0-65a6-4c35-aec0-704be7e504eb
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9025.pdf 9025.pdf (178 Kb)
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Title
Title An Approach for Solving Traveling Salesman Problem using Hybrid Ant Colony Optimization
Language en
Publication date 2011-05-05
Authors
Hlaing, Zar Chi Su Su
Khine, May Aye
Description
Traveling salesman problem (TSP) is one ofthe most famous combinatorial optimization(CO) problems, which has wide applicationbackground. Ant Colony Optimization (ACO) isa heuristic algorithm which has been proven asuccessful technique and applied to a number ofcombinatorial optimization problems and takenas one of the high performance computingmethods for TSP. ACO has very good searchcapability for optimization problems, but it stillhas some drawbacks for solving TSP. Thesedrawbacks will be more obvious when theproblem size increases. The present paperproposes an ACO algorithm with nearestneighbor (NN) heuristic approach andinformation entropy which is conducted on theconfiguration strategy for the adjustableparameters to improve the efficiency of ACO insolving TSP. The performance of ACO alsodepends on the appropriate setting ofparameters. Then, ACO for TSP has beenimproved by incorporating local optimizationheuristic. Algorithms are tested on benchmarkproblems from TSPLIB and test results arepresented. From our experiments, the proposedalgorithm has superior search performance overtraditional ACO algorithms do.
Keywords
ant colony optimization, traveling salesman problem, nearest neighbor heuristic
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/87
Journal articles
Ninth International Conference On Computer Applications (ICCA 2011)
Conference papers
Books/reports/chapters
Thesis/dissertations
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