articleNov 27, 2002Closed access

A modified particle swarm optimizer

Indiana University – Purdue University Indianapolis · University of Indianapolis

Indexed incrossref

Abstract

Evolutionary computation techniques, genetic algorithms, evolutionary strategies and genetic programming are motivated by the evolution of nature. A population of individuals, which encode the problem solutions are manipulated according to the rule of survival of the fittest through "genetic" operations, such as mutation, crossover and reproduction. A best solution is evolved through the generations. In contrast to evolutionary computation techniques, Eberhart and Kennedy developed a different algorithm through simulating social behavior (R.C. Eberhart et al., 1996; R.C. Eberhart and J. Kennedy, 1996; J. Kennedy and R.C. Eberhart, 1995; J. Kennedy, 1997). As in other algorithms, a population of individuals…

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Authors

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Topics & keywords

Keywords
  • Particle swarm optimization
  • Evolutionary computation
  • Crossover
  • Mathematical optimization
  • Population
  • Computer science
  • Mutation
  • Evolutionary algorithm
UN Sustainable Development Goals
  • Partnerships for the goals
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