What Else Is the Evolution of PSO Telling Us?
Open Access
- 28 January 2008
- journal article
- research article
- Published by Hindawi Limited in Journal of Artificial Evolution and Applications
- Vol. 2008, 1-12
- https://doi.org/10.1155/2008/289564
Abstract
Evolutionary algorithms (EAs) can be used in order to design particle swarm optimization (PSO) algorithms that work, in some cases, considerably better than the human-designed ones. By analyzing the evolutionary process of designing PSO algorithms, we can identify different swarm phenomena (such as patterns or rules) that can give us deep insights about the swarm behavior. The rules that have been observed can help us design better PSO algorithms for optimization. We investigate and analyze swarm phenomena by looking into the process of evolving PSO algorithms. Several test problems have been analyzed in the experiments and interesting facts can be inferred from the strategy evolution process (the particle quality could influence the update order, some particles are updated more frequently than others, the initial swarm size is not always optimal).Keywords
This publication has 9 references indexed in Scilit:
- Parallel asynchronous particle swarm optimizationInternational Journal for Numerical Methods in Engineering, 2006
- Evolving Evolutionary Algorithms Using Linear Genetic ProgrammingEvolutionary Computation, 2005
- The particle swarm - explosion, stability, and convergence in a multidimensional complex spaceIEEE Transactions on Evolutionary Computation, 2002
- A comparison of linear genetic programming and neural networks in medical data miningIEEE Transactions on Evolutionary Computation, 2001
- Evolving Teams of Predictors with Linear Genetic ProgrammingGenetic Programming and Evolvable Machines, 2001
- Evolutionary programming made fasterIEEE Transactions on Evolutionary Computation, 1999
- No free lunch theorems for optimizationIEEE Transactions on Evolutionary Computation, 1997
- Ant system: optimization by a colony of cooperating agentsIEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 1996
- Weak Mutation Testing and Completeness of Test SetsIEEE Transactions on Software Engineering, 1982