Quantum-behaved brain storm optimization approach to solving Loney's solenoid problem

  • Haibin Duan*
  • , Cong Li
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Brain storm optimization (BSO) is a novel population-based swarm intelligence algorithm based on the human brainstorming process. BSO has been proven feasible and has been successfully applied to benchmark problems in the electromagnetic field. In this paper, inspired by the mechanism of quantum theories, a novel variant of BSO algorithm, called quantum-behaved BSO (QBSO), is proposed to solve an optimization problem modeled for Loney's solenoid problem. The new mechanism improves the diversity of population and also utilizes the global information to generate the new individual. Simulation results show that QBSO has better ability to jump out of local optima and perform better compared with the basic BSO.

Original languageEnglish
Article number6827252
JournalIEEE Transactions on Magnetics
Volume51
Issue number1
DOIs
StatePublished - 1 Jan 2015

Keywords

  • Brain storm optimization (BSO)
  • optimization
  • optimization benchmark problem
  • quantum-behaved

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