Title :
A collaborative model for tracking optima in dynamic environments
Author :
Lung, Rodica Ioana ; Dumitrescu, D.
Author_Institution :
Babes-Bolyai Univ. of Cluj Napoca, Cluj-Napoca
Abstract :
A new hybrid approach to optimization in dynamic environments called collaborative evolutionary-swarm optimization (CESO) is presented. CESO is a simple method for tracking moving optima in a dynamic environment by combining the search abilities of an evolutionary algorithm for multimodal optimization and a particle swarm optimization algorithm. A collaborative mechanism is designed for the two methods. Numerical experiments indicate CESO to be an efficient method for the selected test problems compared with other evolutionary approaches.
Keywords :
evolutionary computation; particle swarm optimisation; collaborative evolutionary-swarm optimization; collaborative mechanism; collaborative model; dynamic environments; evolutionary algorithm; multimodal optimization; optima tracking; particle swarm optimization algorithm; Collaboration; Convergence; Design optimization; Diversity reception; Evolutionary computation; Lungs; Optimization methods; Particle swarm optimization; Particle tracking; Testing;
Conference_Titel :
Evolutionary Computation, 2007. CEC 2007. IEEE Congress on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-1339-3
Electronic_ISBN :
978-1-4244-1340-9
DOI :
10.1109/CEC.2007.4424520
