Firefly algorithm and pattern search hybridized for global optimization

Mahdiyeh Eslami, Hussain Shareef, Mohammad Khajehzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)


Firefly optimization algorithm is one of the latest swarm intelligence based optimization algorithm. A new hybrid optimization algorithm, which combines pattern search with firefly algorithm, namely FAPS, is proposed for numerical global optimization. There are two alternative phases of the proposed algorithm: the global exploration phase realized by firefly algorithm and the exploitation phase completed by pattern search. The performance of the proposed FAPS algorithm was tested on a comprehensive set of benchmark functions. The numerical experiments demonstrate that the new algorithm has high viability, accuracy and stability and the performance of firefly algorithm is much improved by introducing a pattern search method.

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Technology - 9th International Conference, ICIC 2013, Proceedings
Number of pages7
Publication statusPublished - 2013
Externally publishedYes
Event9th International Conference on Intelligent Computing, ICIC 2013 - Nanning, China
Duration: Jul 28 2013Jul 31 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7996 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference9th International Conference on Intelligent Computing, ICIC 2013


  • firefly algorithm
  • global optimization
  • hybridization
  • pattern search

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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