Title :
An effective dynamic weighted rule for ant colony system optimization
Author :
Lee, SeungGwan ; Jung, TaeUng ; Chung, TaeChoong
Author_Institution :
Dept. of Comput. Eng., Kyung Hee Univ., Seoul, South Korea
Abstract :
The ant colony system (ACS) algorithm is new metaheuristic for hard combinational optimization problems. It is a population-based approach that exploits positive feedback as well as greedy search. It was first proposed for tackling the well known traveling salesman problem (TSP). We introduce a new version of the ACS based on a dynamic weighted updating rule. Implementation to solve TSP and the performance results under various conditions are conducted, and the comparison between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with the original ACS in terms of solution quality and computation speed for these problem
Keywords :
algorithm theory; evolutionary computation; feedback; search problems; travelling salesman problems; ant colony system optimization; computation speed; dynamic weighted rule; dynamic weighted updating rule; greedy search; hard combinational optimization problems; population-based approach; positive feedback; solution quality; traveling salesman problem; Ant colony optimization; Cities and towns; Genetics; Legged locomotion; Neural networks; Simulated annealing; Traveling salesman problems;
Conference_Titel :
Evolutionary Computation, 2001. Proceedings of the 2001 Congress on
Conference_Location :
Seoul
Print_ISBN :
0-7803-6657-3
DOI :
10.1109/CEC.2001.934354
