Title :
An improved simulated annealing andgenetic algorithm for TSP
Author :
Gao Ye ; Xue Rui
Author_Institution :
Sch. of Comput. Sci. & Technol., Xi´an Univ. of Sci. & Technol., Xi´an, China
Abstract :
In order to improve the evolution efficiency and species diversity of traditional genetic algorithm in solving TSP problems, a modified hybrid simulated annealing genetic algorithm is proposed. This algorithm adopts the elite selection operator to ensure not only the diversity of the algorithm but also that groups are always close to the optimal solution; at the same time, places the simulated annealing algorithm in the evolutionary process of genetic algorithm, and using the hybrid algorithm dual criteria to control algorithm´s optimize performance and efficiency simultaneously. The final example shows that the hybrid algorithm is an optimization method with higher optimize performance, efficiency and reliability.
Keywords :
genetic algorithms; simulated annealing; travelling salesman problems; TSP problems; elite selection operator; evolution efficiency; evolutionary process; hybrid algorithm dual criteria; modified hybrid simulated annealing genetic algorithm; optimization method; species diversity; Algorithm design and analysis; Convergence; Genetic algorithms; Simulated annealing; Sociology; Statistics; Elite selection operator; Genetic Algorithm; Simulated annealing algorithm; TSP;
Conference_Titel :
Broadband Network & Multimedia Technology (IC-BNMT), 2013 5th IEEE International Conference on
Conference_Location :
Guilin
DOI :
10.1109/ICBNMT.2013.6823904