Title :
An Efficient Particle Swarm Optimization Approach Based on Cultural Algorithm Applied to Mechanical Design
Author :
Coelho, Leandro Dos Santos ; Mariani, Viviana Cocco
Author_Institution :
Pontifical Catholic Univ. of Parana, Curitiba
Abstract :
Particle swarm optimization (PSO) is a population-based swarm intelligence algorithm driven by the simulation of a social psychological metaphor instead of the survival of the fittest individual. Based on the swarm intelligence theory, this paper discusses the use of PSO approaches using an operator and based on the Gaussian probability distribution function as a population space of a cultural algorithm, called cultural Gaussian PSO (GPSO-CA). Cultural algorithms are mechanisms that incorporate domain knowledge obtained during the evolutionary process, which increase the efficiency of the search process. These approaches are employed in a well-studied continuous optimization problem of mechanical engineering design.
Keywords :
Gaussian processes; evolutionary computation; mechanical engineering; particle swarm optimisation; search problems; statistical distributions; Gaussian probability distribution function; cultural Gaussian particle swarm optimization; cultural algorithm; domain knowledge; evolutionary process; mechanical engineering design; population-based swarm intelligence algorithm; search process; social psychological metaphor; survival-of-the-fittest; Algorithm design and analysis; Cultural differences; Design engineering; Design optimization; Equations; Mechanical engineering; Particle swarm optimization; Probability distribution; Psychology; Random number generation;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688432