DocumentCode
412661
Title
Improving the performance of ACO algorithms by adaptive control of candidate set
Author
Watanabe, Isamu ; Matsui, Shouichi
Author_Institution
Commun. & Inf. Res. Lab., Central Res. Inst. of Electr. Power Ind., Tokyo, Japan
Volume
2
fYear
2003
fDate
8-12 Dec. 2003
Firstpage
1355
Abstract
The performance of ant colony optimization (ACO) algorithms with candidate sets is high for large optimization problems, but it is difficult to set the size of candidate sets to optimal in advance. We propose an adaptive control mechanism of candidate sets based on pheromone concentrations for improving the performance of ACO algorithms and report the results of computational experiments using the graph coloring problems.
Keywords
adaptive control; artificial life; evolutionary computation; graph colouring; optimisation; ACO algorithms; adaptive control mechanism; ant colony optimization algorithms; candidate set; graph coloring problems; optimization problems; Adaptive control; Ant colony optimization; Genetic algorithms; Industrial control; Laboratories; Routing; Runtime; Traveling salesman problems; Vehicle dynamics; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN
0-7803-7804-0
Type
conf
DOI
10.1109/CEC.2003.1299826
Filename
1299826
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