DocumentCode :
694809
Title :
A Hybrid Artificial Bee Colony Algorithm Combined with Simulated Annealing Algorithm for Traveling Salesman Problem
Author :
Pei Shi ; Suling Jia
Author_Institution :
Schcool of Econ. & Manage., Beihang Univ., Beijing, China
fYear :
2013
fDate :
7-8 Dec. 2013
Firstpage :
740
Lastpage :
744
Abstract :
In order to solve travelling salesman problem (TSP), a hybrid artificial bee colony algorithm combined with simulated annealing algorithm (HABC-SA) is presented for TSP. This algorithm gives a discrete coding method for food source position. Crossover and mutation operators in genetic algorithm are introduced into the new algorithm to do local search, Simulated annealing idea is applied in this hybrid artificial bee colony algorithm to increase the diversity of food sources. The proposed algorithm is tested on benchmark problems, and results show that this algorithm can avoid pre-maturity and advance constringency for TSP.
Keywords :
ant colony optimisation; genetic algorithms; simulated annealing; travelling salesman problems; HABC-SA; TSP; artificial bee colony algorithm; crossover operators; discrete coding method; food source position; genetic algorithm; mutation operators; simulated annealing algorithm; traveling salesman problem; Algorithm design and analysis; Cities and towns; Encoding; Genetic algorithms; Particle swarm optimization; Simulated annealing; artificial bee colony algorithm (ABC); simulated annealing idea; travelling salesman problem (TSP);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Cloud Computing Companion (ISCC-C), 2013 International Conference on
Conference_Location :
Guangzhou
Type :
conf
DOI :
10.1109/ISCC-C.2013.13
Filename :
6973680
Link To Document :
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