A modified particle swarm optimization algorithm and its application to the multiobjective FET modeling problem

Authors : Ufuk ÖZKAYA, Filiz GÜNEŞ

Pages : 263-271

View : 14 | Download : 9

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :This paper introduces a modified particle swarm algorithm to handle multiobjective optimization problems. In multiobjective PSO algorithms, the determination of Pareto optimal solutions depends directly on the strategy of assigning a best local guide to each particle. In this work, the PSO algorithm is modified to assign a best local guide to each particle by using minimum angular distance information. This algorithm is implemented to determine field-effect transistor insert ignore into journalissuearticles values(FET); model elements subject to the Pareto domination between the scattering parameters and operation bandwidth. Furthermore, the results are compared with those obtained by the nondominated sorting genetic algorithm-II. FET models are also built for the 3 points sampled from the different locations of the Pareto front, and a discussion is presented for the Pareto relation between the scattering parameter performances and the operation bandwidth for each model.
Keywords : FET modeling, multiobjective optimization, pareto optimal analysis, particle swarm optimization