Chaotic quantum behaved particle swarm optimization algorithm for solving nonlinear system of equations

Turgut O. E., Turgut M. S., ÇOBAN M. T.

COMPUTERS & MATHEMATICS WITH APPLICATIONS, vol.68, no.4, pp.508-530, 2014 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 68 Issue: 4
  • Publication Date: 2014
  • Doi Number: 10.1016/j.camwa.2014.06.013
  • Journal Name: COMPUTERS & MATHEMATICS WITH APPLICATIONS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.508-530
  • Keywords: Chaotic maps, Metaheuristics, Nonlinear system of equations, Optimization methods, Quantum behaved particle swarm optimization, Root solvers, IMPERIALIST COMPETITIVE ALGORITHM, PARAMETER-IDENTIFICATION, GENETIC ALGORITHMS, STABILITY
  • Dokuz Eylül University Affiliated: Yes

Abstract

This study proposes a novel chaotic quantum behaved particle swarm optimization algorithm for solving nonlinear system of equations. Different chaotic maps are introduced to enhance the effectiveness and robustness of the algorithm. Several benchmark studies are carried out. Logistic map gives the best results and is utilized in solving nonlinear equation sets. Nine well known problems are solved with our algorithm and results are compared with Quantum Behaved Particle Swarm Optimization, Intelligent Tuned Harmony Search, Gravitational Search Algorithm and literature studies. Comparison results reveal that the proposed algorithm can cope with the highly non-linear problems and outperforms many algorithms which exist in the literature. (C) 2014 Elsevier Ltd. All rights reserved.