Owl search algorithm: A novel nature-inspired heuristic paradigm for global optimization
- 22 March 2018
- journal article
- conference paper
- Published by IOS Press in Journal of Intelligent & Fuzzy Systems
- Vol. 34 (3), 1573-1582
- https://doi.org/10.3233/JIFS-169452
Abstract
This paper presents, a novel nature-inspired optimization paradigm, named as owl search algorithm (OSA) for solving global optimization problems. The OSA is a population based technique based on the hunting mechanism of the owls in dark. The proposedKeywords
This publication has 23 references indexed in Scilit:
- A new optimization method: Dolphin echolocationAdvances in Engineering Software, 2013
- Krill herd: A new bio-inspired optimization algorithmCommunications in Nonlinear Science and Numerical Simulation, 2012
- Model-reference robust tuning of 2DoF PI controllers for first- and second-order plus dead-time controlled processesJournal of Process Control, 2012
- A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithmsSwarm and Evolutionary Computation, 2011
- A New Metaheuristic Bat-Inspired AlgorithmPublished by Springer Science and Business Media LLC ,2010
- Web-based Virtual Research EnvironmentsPublished by Springer Science and Business Media LLC ,2009
- GSA: A Gravitational Search AlgorithmInformation Sciences, 2009
- Metaheuristics for Multiobjective OptimizationPublished by Wiley ,2009
- A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithmJournal of Global Optimization, 2007
- No free lunch theorems for optimizationIEEE Transactions on Evolutionary Computation, 1997