A new metaheuristic for numerical function optimization: Vortex Search algorithm

Berat Doʇan*, Tamer Ölmez

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

311 Citations (Scopus)

Abstract

In this study, a new single-solution based metaheuristic, namely the Vortex Search (VS) algorithm, is proposed to perform numerical function optimization. The proposed VS algorithm is inspired from the vortex pattern created by the vortical flow of the stirred fluids. To provide a good balance between the explorative and exploitative behavior of a search, the proposed method models its search behavior as a vortex pattern by using an adaptive step size adjustment scheme. The proposed VS algorithm is tested over 50 benchmark mathematical functions and the results are compared to both the single-solution based (Simulated Annealing, SA and Pattern Search, PS) and population-based (Particle Swarm Optimization, PSO2011 and Artificial Bee Colony, ABC) algorithms. A Wilcoxon-Signed Rank Test is performed to measure the pair-wise statistical performances of the algorithms, the results of which indicate that the proposed VS algorithm outperforms the SA, PS and ABC algorithms while being competitive with the PSO2011 algorithm.

Original languageEnglish
Pages (from-to)125-145
Number of pages21
JournalInformation Sciences
Volume293
DOIs
Publication statusPublished - 1 Feb 2015

Bibliographical note

Publisher Copyright:
© 2014 Elsevier Inc. All rights reserved.

Keywords

  • Artificial bee colony
  • Function optimization
  • Global optimization
  • Metaheuristics
  • Particle swarm optimization
  • Simulated annealing

Fingerprint

Dive into the research topics of 'A new metaheuristic for numerical function optimization: Vortex Search algorithm'. Together they form a unique fingerprint.

Cite this