A hybrid cultural algorithm with local search for traveling salesman problem

Authors:
Yongjun Kim;Sung-Bae Cho
Affiliations:
Department of Computer Science, Yonsei University, Seoul, Korea;Department of Computer Science, Yonsei University, Seoul, Korea
Venue:
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
Year:
2009

Citing 6
Cited 0

Applying evolutionary programming to selected traveling salesman problems

Cybernetics and Systems
Improved Ant Colony Algorithm and its Applications in TSP

ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
An Angle-Based Crossover Tabu Search for the Traveling Salesman Problem

ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 04
Applying adaptive algorithms to epistatic domains

IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Computing with the social fabric: The evolution of social intelligence within a cultural framework

IEEE Computational Intelligence Magazine
Solving the traveling salesman problem with annealing-based heuristics: a computational study

IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans

Quantified Score

Hi-index	0.00

Visualization

Abstract

A new Hybrid Cultural Algorithm with Local Search (HCALS) is introduced to solve Traveling Salesman Problem (TSP). The algorithm integrates the local search method into the cultural algorithm which uses social intelligence to guide and lead individuals in the population. Better solutions can be attained by controlling individuals which are locally optimized by the local search methods. The combination of these two methods can be a promising method for solving the combinatorial problems like TSP. The experimental results show that the proposed algorithm can find better solutions than other methods for TSP in most cases.