Particle swarm optimization combined with normative knowledge applied to Loney's solenoid design

• Leandro dos Santos Coelho ^[1] ; Piergiorgio Alotto ^[2]
  1. [1] Pontifícia Universidade Católica do Paraná

     Pontifícia Universidade Católica do Paraná

     Brasil

     
  2. [2] Università di Padova
• Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 28, Nº 5 (Special Issue: Selected Papers from OIPE 2008), 2009, págs. 1155-1161
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • Purpose – The purpose of this paper is to show, on a widely used benchmark problem, that normative knowledge concepts can be incorporated into particle swarm optimization (PSO) algorithms in order to improve their search ability.

    Design/methodology/approach – Normative knowledge concepts are used within the framework of PSO algorithms in order to influence the cognitive and social components of the particle behaviour.

    Findings – It is shown that the proposed algorithm can significantly improve the performance of PSO on the selected benchmark problem, in terms of both best and average solutions.

    Research limitations/implications – Although the chosen benchmark is considered to be representative of typical electromagnetic problems, different test cases may give less satisfactory results.

    Practical implications – The proposed approach appears to be an efficient general purpose stochastic optimizer for electromagnetic design problems.

    Originality/value – This paper introduces the use of normative knowledge concepts to control the cognitive and social components of PSO algorithms.