Abstract: This paper suggests the use of dynamic population size throughout the optimization process which is applied on the numerical model of a medium voltage post insulator. The main objective of the dynamic population is reducing population size, to achieve faster convergence. Change of population size can be done in any iteration by proposed method. The multiobjective optimization process is based on the PSO algorithm, which is suitably modifiedin order to operate with the principle of the optimal Pareto front.Keywords: dynamic population size, insulation elements, multi-objective optimization, particle swarm optimizationPublished: 10.07.2015; Views: 802; Downloads: 17 Link to full text
Abstract: This paper studies the efficiency of a recently defined population-based direct global optimization method called Differential Evolution with self-adaptive control parameters. The original version uses fixed population size but a method for gradually reducing population size is proposed in this paper. It improves the efficiency and robustness of the algorithm and can be applied to any variant of a Differential Evolution algorithm. The proposed modification is tested on commonly used benchmark problems for unconstrained optimization and compared with other optimization methods such as Evolutionary Algorithms and Evolution Strategies.Keywords: differential evolution, control parameter, fitness function, global function optimization, self-adaptation, population sizePublished: 01.06.2012; Views: 1400; Downloads: 95 Link to full text
