Title :
Efficiency of Local Genetic Algorithm in Parallel Processing
Author :
Gang, Peng ; Iimura, Ichiro ; Nakatsuru, Takeshi ; Nakayama, Shigeru
Author_Institution :
Oita National College of Technology Maki, Oita City, Japan
Abstract :
This paper discusses a parallel genetic algorithm (GA) which focuses on the local operator for Traveling salesman problem (TSP). The local operator is a simple GA named as Local Genetic Algorithm (LGA). The LGA is combined to another GA named as Global Genetic Algorithm (GGA). It increases the computational time running a GA as a local operator in another one. To solve this problem, we build a parallel system based on our previous works for running the LGA to speed up the process. The results show that LGA improve the search quality significantly and it is more efficient running LGA with parallel system than single CPU.
Keywords :
Traveling Salesman Problem; genetic algorithm (GA); global GA; local GA; object shared space; parallel GA; Cities and towns; Computer science; Concurrent computing; Control engineering; Control engineering computing; Educational institutions; Genetic algorithms; Genetic mutations; Parallel processing; Traveling salesman problems; Traveling Salesman Problem; genetic algorithm (GA); global GA; local GA; object shared space; parallel GA;
Conference_Titel :
Parallel and Distributed Computing, Applications and Technologies, 2005. PDCAT 2005. Sixth International Conference on
Print_ISBN :
0-7695-2405-2
DOI :
10.1109/PDCAT.2005.129