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
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;
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
DOI :
10.1109/IPTC.2010.9