Title :
An improved niche ant colony algorithm for multi-modal function optimization
Author :
Zhang, Xinming ; Wang, Lirong ; Huang, Bingyi
Author_Institution :
Shenzhen Grad. Sch., Harbin Inst. of Technol., Shenzhen, China
Abstract :
In this paper, to overcome the premature defect of traditional ant colony algorithm, a new improved niche ant colony algorithm (niche ant colony algorithm based on the fitness sharing principle) is proposed by combining the fitness sharing method with niche ant colony algorithm and applied to the multi-modal function optimization problem. The comparison between the results obtained by the improved niche ant colony algorithm (INACA) and the results found by traditional ant colony algorithm(ACA) and niche genetic algorithm(NGA) shows that the former has higher effectiveness and superiority in global optimization.
Keywords :
ant colony optimisation; INACA; fitness sharing method; global optimization; improved niche ant colony algorithm; multimodal function optimization problem; Algorithm design and analysis; Computers; Educational institutions; Gallium nitride; Genetic algorithms; Heuristic algorithms; Optimization; fitness sharing; improved niche ant colony algorithm; multi-modal function optimization;
Conference_Titel :
Instrumentation & Measurement, Sensor Network and Automation (IMSNA), 2012 International Symposium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4673-2465-6
DOI :
10.1109/MSNA.2012.6324605
