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

Authors

UFUK ÖZKAYA
FİLİZ GÜNEŞ

DOI

10.3906/elk-1102-1032

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 (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

First Page

263

Last Page

271

Recommended Citation

ÖZKAYA, UFUK and GÜNEŞ, FİLİZ (2012) "A modified particle swarm optimization algorithm and its application to the multiobjective FET modeling problem," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 20: No. 2, Article 7. https://doi.org/10.3906/elk-1102-1032
Available at: https://journals.tubitak.gov.tr/elektrik/vol20/iss2/7