Geodesy

Evolutionary algorithm

Engineering optimization

Metaheuristic

Algorithm

Benchmark (surveying)

Pure mathematics

Biology

Optimization algorithm

Field (mathematics)

Computer science

Mathematical optimization

Paleontology

Mathematics

Geography

Artificial intelligence

Jackal

Optimization problem

Expert Systems with Applications

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 the golden 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.

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