IITA'09 Proceedings of the 3rd international conference on Intelligent information technology application
A study of parallel and distributed particle swarm optimization methods
Proceedings of the 2nd workshop on Bio-inspired algorithms for distributed systems
An empirical comparison of parallel and distributed particle swarm optimization methods
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Constraint Handling in Particle Swarm Optimization
International Journal of Swarm Intelligence Research
A Multiobjective Particle Swarm Optimizer for Constrained Optimization
International Journal of Swarm Intelligence Research
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was derived from the original particle swarm optimization (PSO), which is incorporated with the genetic reproduction mechanisms, namely crossover and mutation. Based on which a modified genetic particle swarm optimization (MGPSO) was introduced to solve constrained optimization problems. In which the differential evolution (DE) was incorporated into GPSO to enhance search performance. At each generation GPSO and DE generated a position for each particle, respectively, and the better one was accepted to be a new position for the particle. To compare and ranking the particles, the lexicographic order ranking was introduced. Moreover, DE was incorporated to the original PSO with the same method, which was used to be compared with MGSPO. MGPSO were experimented with wellknown benchmark functions. By comparison with original PSO algorithms and the evolution strategy, the simulation results have shown its robust and consistent effectiveness. Index Terms Particle swarm optimization, genetic algorithm, constrained optimization.