Advances in Particle Swarm Algorithms in Asynchronous, Discrete and Multi-Objective Optimization
This lecture presents the latest advancement of Particle Swarm Optimization (PSO) in asynchronous update, discrete, and multi-objective problems. PSO is a population based stochastic optimization algorithm, inspired by the social behavior of bird flocking and fish schooling. PSO has been introduce...
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| Format: | Conference or Workshop Item |
| Language: | English |
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2014
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| Online Access: | http://umpir.ump.edu.my/id/eprint/8296/ http://umpir.ump.edu.my/id/eprint/8296/ http://umpir.ump.edu.my/id/eprint/8296/1/Advances_in_Particle_Swarm_Algorithms_in_Asynchronous%2C_Discrete_and_MultiObjective_Optimization.pdf |
| Summary: | This lecture presents the latest advancement of Particle Swarm Optimization (PSO) in asynchronous update,
discrete, and multi-objective problems. PSO is a population based stochastic optimization algorithm, inspired
by the social behavior of bird flocking and fish schooling. PSO has been introduced by Kennedy and
Eberhart and contains a group of particles that move in a search space searching for an optimum solution
according to a particular objective function. The movement of a particle is subjected to its own best found
solution, pBest, and the best found solution in the neighborhood, gBest.
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