Title :
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
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;
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
DOI :
10.1109/CloudCom.2012.6427528
