Integrated genetic algorithms and cloud technology to solve travelling salesman problem on Hadoop

Author

Yi-Chieh Shen ; Chi-Hang Hsu ; Sung-Huai Hsieh

Author_Institution

Dept. of Comput. Sci. & Inf. Eng., Providence Univ., Taichung, Taiwan

fYear

2012

fDate

3-6 Dec. 2012

Firstpage

566

Lastpage

569

Abstract

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. Hadoop is one of the most common cloud computing platform in large-scale commercial environment. Complete and strong infrastructure which can help us reduced much development time. We use genetic algorithm solved traveling salesman problem on Hadoop platform to save huge computing processes and time.

Keywords

cloud computing; genetic algorithms; travelling salesman problems; Hadoop platform; cloud computing platform; cloud technology; crossover operators; evolutionary technique; fittest survival; integrated genetic algorithms; mutation operators; optimization problems; travelling salesman problem; Cities and towns; Cloud computing; Conferences; Genetic algorithms; Time measurement; Traveling salesman problems; Cloud Technology; Distributed Computing; Genetic Algorithms; Hadoop; TSP; Traveling Salesman;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on

Conference_Location

Taipei

Print_ISBN

978-1-4673-4511-8

Electronic_ISBN

978-1-4673-4509-5

Type

conf

DOI

10.1109/CloudCom.2012.6427528

Filename

6427528