DocumentCode :
3515239
Title :
Solving Multi-objective Optimization Problems with Chaotic Ant Swarm
Author :
Han, Renmin ; Huang, Jun ; Wang, Junping ; Guo, Danqing
Author_Institution :
Sch. of software, Beijing Univ. of Posts & Telecommun., Beijing, China
fYear :
2010
fDate :
28-29 Oct. 2010
Firstpage :
83
Lastpage :
87
Abstract :
Chaotic Ant Swarm is a recently new and promising algorithm of Optimization Problem based on the chaotic theory and foraging food processing of ants. This paper proposes a Multi-Objective Optimization version of CAS, named MOCAS, by changing the colony behavior organization. The proposed algorithm also introduced a re-distribution operation that ensures the uniform distribution of final result. We have validated it by several test functions taken from the standard literature. The results are exciting and show the competitiveness in multi-objective optimization.
Keywords :
chaos; optimisation; MOCAS; chaotic ant swarm; chaotic theory; colony behavior organization; multiobjective optimization problem; optimization problem; Chaos; Equations; Mathematical model; Neodymium; Optimization; Organizations; Proposals; Chaotic Ant Swarm; Pareto-optimal solutions; multiobjective optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligence Information Processing and Trusted Computing (IPTC), 2010 International Symposium on
Conference_Location :
Huanggang
Print_ISBN :
978-1-4244-8148-4
Electronic_ISBN :
978-0-7695-4196-9
Type :
conf
DOI :
10.1109/IPTC.2010.9
Filename :
5663176
Link To Document :
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