Golden jackal optimization: A novel nature-inspired optimizer for engineering applications

•Developed Golden Jackal Optimization (GJO) Algorithm as an optimization method.•Tested the performance of proposed algorithm against mathematical and engineering benchmarks.•Compared proposed algorithm with other well-known optimization algorithms.•Conducted statistical analyses.•Demonstrated super...

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Bibliographic Details
Published inExpert systems with applications Vol. 198; p. 116924
Main Authors Chopra, Nitish, Mohsin Ansari, Muhammad
Format Journal Article
LanguageEnglish
Published New York Elsevier Ltd 15.07.2022
Elsevier BV
Subjects
Constrained problems
Design engineering
Electrical engineering
GJO
Golden Jackal optimization
Heuristic methods
Metaheuristic
Nature-inspired algorithm
Optimization
Optimization algorithm
Search algorithms
Constrained problems
Metaheuristic
Optimization algorithm
Nature-inspired algorithm
GJO
Golden Jackal optimization
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Summary:•Developed Golden Jackal Optimization (GJO) Algorithm as an optimization method.•Tested the performance of proposed algorithm against mathematical and engineering benchmarks.•Compared proposed algorithm with other well-known optimization algorithms.•Conducted statistical analyses.•Demonstrated superiority of proposed algorithm in various conditions. A new nature-inspired optimization method, named the Golden Jackal Optimization (GJO) algorithm is proposed, which aims to provide an alternative optimization method for solving real-world engineering problems. GJO is inspired by the collaborative hunting behaviour of thegolden jackals(Canis aureus). The three elementary steps of algorithm are prey searching, enclosing, and pouncing, which are mathematically modelled and applied. The ability of proposed algorithm is assessed, by comparing with different state of the art metaheuristics, on benchmark functions. The proposed algorithm is further tested for solving seven different engineering design problems and introduces a real implementation of the proposed method in the field of electrical engineering. The results of the classical engineering design problems and real implementation verify that the proposed algorithm is appropriate for tackling challenging problems with unidentified search spaces.
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ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2022.116924