Title :
A Novel Genetic Algorithm for Traveling Salesman Problem Based on Neighborhood Code
Author :
Yang, Jin-Qiu ; Yang, Jian-Gang
Author_Institution :
Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China
Abstract :
Classic genetic algorithm is not suitable to solve traveling salesman problem, because the encoding of the traveling salesman problem is either the permutations of the cities or the combinations of edges, which can not be directly operated by ordinary crossover or mutation operators. This paper introduces a novel encoding for traveling salesman problem, which can be operated by the ordinary crossover and mutation operators; and in order to accelerate the rate of the convergence, a novel local improvement approach is also presented.
Keywords :
genetic algorithms; travelling salesman problems; NP-hard combinatorial problem; genetic algorithm; local improvement approach; mutation operators; neighborhood code; ordinary crossover; traveling salesman problem; Acceleration; Cities and towns; Computer science; Educational institutions; Encoding; Genetic algorithms; Genetic mutations; Intelligent networks; Intelligent systems; Traveling salesman problems; combinatorial optimization; genetic algorithm; neighborhood code; traveling salesman problem;
Conference_Titel :
Intelligent Networks and Intelligent Systems, 2009. ICINIS '09. Second International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-1-4244-5557-7
Electronic_ISBN :
978-0-7695-3852-5
DOI :
10.1109/ICINIS.2009.116