Red fox optimization algorithm

Fox is very popular in various regions of the Globe, where representatives of this kind can be found in Europe, Asia, North America, and even in some arctic regions. The way this predator lives and hunts is very peculiar. It is active all year round, traversing the lands in hunting both for differen...

Full description

Saved in:
Bibliographic Details
Published in:Expert systems with applications Vol. 166; p. 114107
Main Authors: Połap, Dawid, Woźniak, Marcin
Format: Journal Article
Language:English
Published: New York Elsevier Ltd 15.03.2021
Elsevier BV
Subjects:
Algorithms
Changing environments
Foxes
Global optimization
Heuristic methods
Hunting
Ice environments
Meta-heuristic
Optimization
Optimization algorithms
Wild animals
90C59
Meta-heuristic
80M50
Optimization
ISSN:0957-4174, 1873-6793
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Fox is very popular in various regions of the Globe, where representatives of this kind can be found in Europe, Asia, North America, and even in some arctic regions. The way this predator lives and hunts is very peculiar. It is active all year round, traversing the lands in hunting both for different domestic and wild animals. In his strategy fox is using various tricks to distract prey while creeping what makes him a very efficient predator. The territorial habits and family relations between young and adult made the fox easily adaptable to various conditions and therefore helped him to survive in a changing environment. In this article we propose a mathematical model of red fox habits, searching for food, hunting, and developing population while escaping from hunters. Described model is based on local and global optimization method with a reproduction mechanism. The novel model developed for optimization purposes we name the Red Fox Optimization Algorithm (RFO). The proposed method was subjected to benchmark tests using 22 test functions and 7 classic engineering optimization problems. Experimental results are compared to other meta-heuristic algorithms to show potential advantages. •Optimization paradigm based on mathematical model of red fox live and hunting behavior.•Efficient mechanisms of movement, hunting and developing population.•Fast convergence to the optimum and high efficiency in various optimization problems.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2020.114107