Soft Computing

, Volume 21, Issue 17, pp 5091–5102 | Cite as

Firefly algorithm with adaptive control parameters

  • Hui Wang
  • Xinyu Zhou
  • Hui Sun
  • Xiang Yu
  • Jia Zhao
  • Hai Zhang
  • Laizhong Cui
Methodologies and Application

Abstract

Firefly algorithm (FA) is a new swarm intelligence optimization method, which has shown good search abilities on many optimization problems. However, the performance of FA highly depends on its control parameters. In this paper, we investigate the control parameters of FA, and propose a modified FA called FA with adaptive control parameters (ApFA). To verify the performance of ApFA, experiments are conducted on a set of well-known benchmark problems. Results show that the ApFA outperforms the standard FA and five other recently proposed FA variants.

Keywords

Firefly algorithm (FA) Swarm intelligence Adaptive control parameters Self-adaptive FA Global optimization 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Hui Wang
    • 1
    • 2
  • Xinyu Zhou
    • 3
  • Hui Sun
    • 2
  • Xiang Yu
    • 2
  • Jia Zhao
    • 2
  • Hai Zhang
    • 2
  • Laizhong Cui
    • 4
  1. 1.School of Computer and SoftwareNanjing University of Information Science and TechnologyNanjingChina
  2. 2.School of Information EngineeringNanchang Institute of TechnologyNanchangChina
  3. 3.College of Computer and Information EngineeringJiangxi Normal UniversityNanchangChina
  4. 4.College of Computer Science and Software EngineeringShenzhen UniversityShenzhenChina

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