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Instance: Shi1998

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AUTHORS Shi, Y., Eberhart, R.
bibtex-reference @INPROCEEDINGS{Shi1998, author={Yuhui Shi and Eberhart, R.}, booktitle={Evolutionary Computation Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on}, title={A modified particle swarm optimizer}, year={1998}, pages={69-73}, 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 ÒgeneticÓ 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 exists. This algorithm is called particle swarm optimization (PSO) since it resembles a school of flying birds. In a particle swarm optimizer, instead of using genetic operators, these individuals are ÒevolvedÓ by cooperation and competition among the individuals themselves through generations. Each particle adjusts its flying according to its own flying experience and its companions' flying experience. We introduce a new parameter, called inertia weight, into the original particle swarm optimizer. Simulations have been done to illustrate the significant and effective impact of this new parameter on the particle swarm optimizer}, keywords={genetic algorithms;iterative methods;search problems;competition;cooperation;evolutionary computation techniques;evolutionary strategies;flying birds;flying experience;genetic algorithms;genetic programming;inertia weight;modified particle swarm optimizer;particle swarm optimization;social behavior simulation;survival of the fittest;Birds;Collaboration;Computational modeling;Educational institutions;Evolutionary computation;Genetic algorithms;Genetic mutations;Genetic programming;Nonlinear equations;Particle swarm optimization}, doi={10.1109/ICEC.1998.699146},}
label Shi1998
original-source-url http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=699146
standard-reference Y. Shi, R.C. Eberchart, A modified particle swarm optimizer, in: Proceedings of IEEE International Conference on Evolutionary Computation, Anchorage, AK, 1998, pp.69-73.

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