Abstract
The performance of particle swarm optimization using an inertia weight is compared with performance using a constriction factor. Five benchmark functions are used for the comparison. It is concluded that the best approach is to use the constriction factor while limiting the maximum velocity Vmax to the dynamic range of the variable Xmax on each dimension. This approach provides performance on the benchmark functions superior to any other published results known by the authors.
Keywords
InertiaBenchmark (surveying)ConstrictionParticle swarm optimizationDimension (graph theory)LimitingRange (aeronautics)Variable (mathematics)Mathematical optimizationMathematicsComputer scienceControl theory (sociology)PhysicsMathematical analysisMaterials scienceEngineeringArtificial intelligenceClassical mechanicsMechanical engineeringBiology
Affiliated Institutions
Related Publications
A new optimizer using particle swarm theory
The optimization of nonlinear functions using particle swarm methodology is described. Implementations of two paradigms are discussed and compared, including a recently develope...
Particle swarm optimization
The base isolation design usually used the historical well-known earthquake records as an input ground motion. Through the adjustment on each variables of the structure system, ...
A modified particle swarm optimizer
Evolutionary computation techniques, genetic algorithms, evolutionary strategies and genetic programming are motivated by the evolution of nature. A population of individuals, w...
Handbook of Genetic Algorithms
This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems. The first objective is tackled by the editor, Lawrence Davis. Th...
Role of range and precision of the independent variable in regression of data
Abstract Regression of the experimental data of one independent variable, y vs . a linear combination of functions of an independent variable of the form y = Σβ j f j (x) is con...
Publication Info
- Year
- 2002
- Type
- article
- Volume
- 1
- Pages
- 84-88
- Citations
- 2939
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
2939
OpenAlex
Cite This
R.C. Eberhart,
Yan Shi
(2002).
Comparing inertia weights and constriction factors in particle swarm optimization.
, 1
, 84-88.
https://doi.org/10.1109/cec.2000.870279
Identifiers
- DOI
- 10.1109/cec.2000.870279