Title :
A Novel Genetic Algorithm and Its Application in TSP
Author :
Liu, Yanbing ; Huang, Jun
Abstract :
A novel was proposed for the defections of slow convergence and liable to "premature" of traditional GA. It creates crossover and mutation by merging two kinds of heuristics respectively so as to improve the local search ability of GA, and then imports the exterior best-individual set to increase the diversity of the group. The further theoretical analysis and discussion was carried out. simulation results indicated that it can get high-quality solution and consume less running time.
Keywords :
genetic algorithms; travelling salesman problems; genetic algorithm; local search ability; traveling salesman problem; Circuit testing; Cities and towns; Computational modeling; Equations; Genetic algorithms; Genetic mutations; Neural networks; Parallel processing; Particle swarm optimization; Traveling salesman problems; TSP; genetic algorithm; optimization;
Conference_Titel :
Network and Parallel Computing, 2008. NPC 2008. IFIP International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3354-4
DOI :
10.1109/NPC.2008.27
