Title :
Solving TSP with Shuffled Frog-Leaping Algorithm
Author :
Luo Xue-hui ; Yang Ye ; Li Xia
Author_Institution :
Coll. of Inf. Eng., Shenzhen Univ., Shenzhen
Abstract :
Shuffled frog-leaping algorithm (SFLA) is a new memetic meta-heuristic algorithm with efficient mathematical function and global search capability. Traveling salesman problem (TSP) is a complex combinatorial optimization problem, which is typically used as benchmark for testing the effectiveness as well as the efficiency of a newly proposed optimization algorithm. When applying the shuffled frog-leaping algorithm in TSP, memeplex and submemeplex are built and the evolution of the algorithm, especially the local exploration in submemeplex is carefully adapted based on the prototype SFLA. Experimental results show that the shuffled frog leaping algorithm is efficient for small-scale TSP. Particularly for TSP with 51 cities, the algorithm manages to find six tours which are shorter than the optimal tour provided by TSPLIB. The shortest tour length is 428.87 instead of 429.98 which can be found cited elsewhere.
Keywords :
search problems; travelling salesman problems; TSP; complex combinatorial optimization problem; efficient mathematical function; global search capability; memeplex; memetic meta-heuristic algorithm; shuffled frog-leaping algorithm; submemeplex; traveling salesman problem; Ant colony optimization; Benchmark testing; Cities and towns; Design engineering; Educational institutions; Intelligent systems; Prototypes; Space exploration; Traveling salesman problems; Water resources; optimization; shuffled frog leaping algorith; traveling salesman problem;
Conference_Titel :
Intelligent Systems Design and Applications, 2008. ISDA '08. Eighth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-0-7695-3382-7
DOI :
10.1109/ISDA.2008.346