Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Multiobjective optimization using dynamic neighborhood particle swarm optimization
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Particle swarm optimization for minimax problems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Particle swarm optimization for integer programming
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
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Using traditional methods, finding the weights that allow shaping a desired radiation diagram for an antenna in order to reject unwanted signals or maximize the desired signal reception, is possible. However, neither by iterative nor closed methods, can it be done while restricting the amplitudes and phases to a set of finite values for each of them. Also, it often happens that they cannot include in its formulation other types of specifications that are necessary to be achieved. Some modifications were implemented in the method Particle Swarm Optimization (PSO), which reduced the convergence time, especially in the search space of phases where there exists a periodicity that the original method does not take into account. PSO is an evolutionary algorithm, inspired by the social behavior of flocks of birds or fish, developed by Eberhart and Kennedy in 1995, and has been intensively applied in solving numerical Engineering problems.