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  1. University of Computer Studies, Yangon
  2. Conferences

Genetic algorithm for Travelling Salesman Problem using MapReduce

http://hdl.handle.net/20.500.12678/0000004938
21892a57-5e69-4fca-9d7a-71c114549c8d
c4bc87fb-5458-4cf9-80d2-5fd6ab971b8e
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Publication type Article
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Title
Genetic algorithm for Travelling Salesman Problem using MapReduce
en
Publication date 2013-02-26
Authors
Lwin, Hnin Thant
Description
The Travelling Salesman Problem (TSP) is one of the hardest and the most fundamental problems in Computer Science. Although several techniques have been used in the past to reduce the running time of TSP, Genetic algorithms can reduce the running times of NP-complete problems substantially and have the capability of being parallelized. MapReduce is a parallel programming paradigm currently use and Hadoop is one of the most popular MapReduce frameworks because its robust, well designed and scalable file system. In this paper we use a genetic algorithm and parallelizing it on MapReduce Hadoop framework to reduce the running time of Travelling Salesman Problem.
Journal articles
Eleventh International Conference On Computer Applications (ICCA 2013)
Conference papers
Books/reports/chapters
Thesis/dissertations
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