Firefly algorithm with adaptive control parameters

被引：1
|
作者：
Hui Wang
Xinyu Zhou
Hui Sun
Xiang Yu
Jia Zhao
Hai Zhang
Laizhong Cui
机构：
[1] Nanjing University of Information Science and Technology,School of Computer and Software
[2] Nanchang Institute of Technology,School of Information Engineering
[3] Jiangxi Normal University,College of Computer and Information Engineering
[4] Shenzhen University,College of Computer Science and Software Engineering
来源：
Soft Computing | 2017年 / 21卷
关键词：
Firefly algorithm (FA); Swarm intelligence; Adaptive control parameters; Self-adaptive FA; Global optimization;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
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.
引用
收藏
页码：5091 / 5102
页数：11
相关论文
共 50 条
  • [31] Selection of parameters for advanced machining processes using firefly algorithm
    Shukla, Rajkamal
    Singh, Dinesh
    ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH, 2017, 20 (01): : 212 - 221
  • [32] Learning Parameters in Deep Belief Networks Through Firefly Algorithm
    Rosa, Gustavo
    Papa, Joao
    Costa, Kelton
    Passos, Leandro
    Pereira, Clayton
    Yang, Xin-She
    ARTIFICIAL NEURAL NETWORKS IN PATTERN RECOGNITION, 2016, 9896 : 138 - 149
  • [33] An Evolutionary Firefly Algorithm for the Estimation of Nonlinear Biological Model Parameters
    Abdullah, Afnizanfaizal
    Deris, Safaai
    Anwar, Sohail
    Arjunan, Satya N. V.
    PLOS ONE, 2013, 8 (03):
  • [34] Genetic Algorithm Based Quantum Circuit Synthesis with Adaptive Parameters Control
    Ruican, Cristian
    Udrescu, Mihai
    Prodan, Lucian
    Vladutiu, Mircea
    2009 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-5, 2009, : 896 - 903
  • [35] Estimation of vehicle status parameters based on compensation adaptive control algorithm
    Lin, Cheng
    Zhou, Fengjun
    Xu, Zhifeng
    Cao, Wanke
    Dong, Aidao
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2014, 45 (11): : 1 - 8
  • [36] A Modified Differential Evolution Algorithm with Self-adaptive Control Parameters
    Wu Zhi-Feng
    Huang Hou-Kuan
    Yang Bei
    Zhang Ying
    2008 3RD INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM AND KNOWLEDGE ENGINEERING, VOLS 1 AND 2, 2008, : 524 - 527
  • [37] ADAPTIVE PREDICTIVE CONTROL ALGORITHM FOR COMPENSATION OF PARAMETERS OF A POWER ELECTRONICS SYSTEM
    FICARRA, M
    RODELLAR, J
    BORDONAU, J
    PERACAULA, J
    ELECTRONICS LETTERS, 1995, 31 (04) : 329 - 330
  • [38] Parameter optimization of PID controller for water and fertilizer control system based on partial attraction adaptive firefly algorithm
    Mingqi Huang
    Min Tian
    Yang Liu
    Yao Zhang
    Jie Zhou
    Scientific Reports, 12
  • [39] Parameter optimization of PID controller for water and fertilizer control system based on partial attraction adaptive firefly algorithm
    Huang, Mingqi
    Tian, Min
    Liu, Yang
    Zhang, Yao
    Zhou, Jie
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [40] Adaptive local neighborhood range based firefly algorithm for link prediction
    Srilatha, P.
    Ramasubbareddy, Somula
    Sudheer, Devulapalli
    INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2021,
12345