Fractional-order quantum particle swarm optimization

Lai Xu, Aamir Muhammad, Yifei Pu, Jiliu Zhou and Yi Zhang

PLOS ONE, 2019, vol. 14, issue 6, 1-16

Abstract: Motivated by the concepts of quantum mechanics and particle swarm optimization (PSO), quantum-behaved particle swarm optimization (QPSO) was developed to achieve better global search ability. This paper proposes a new method to improve the global search ability of QPSO with fractional calculus (FC). Based on one of the most frequently used fractional differential definitions, the Grünwald-Letnikov definition, we introduce its discrete expression into the position updating of QPSO. Extensive experiments on well-known benchmark functions were performed to evaluate the performance of the proposed fractional-order quantum particle swarm optimization (FQPSO). The experimental results demonstrate its superior ability in achieving optimal solutions for several different optimizations.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0218285

DOI: 10.1371/journal.pone.0218285

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