FOX: a FOX-inspired optimization algorithm

This paper proposes a novel nature-inspired optimization algorithm called the Fox optimizer (FOX) which mimics foraging behavior of foxes in nature when hunting preys. The is based on techniques for measuring distance between fox and its prey to execute an efficient jump. After presenting mathematical models FOX, five classical benchmark functions CEC2019 test are used evaluate it’s performance. FOX also compared against Dragonfly Algorithm (DA), Particle Swarm Optimization (PSO), Fitness Dependent Optimizer (FDO), Grey Wolf (GWO), Whale (WOA), Chimp (ChOA), Butterfly (BOA) Genetic (GA). results indicate that outperforms above-mentioned algorithms. Subsequently, Wilcoxon rank-sum ensure better than comparative algorithms statistically significant manner. Additionally, parameter sensitivity analysis conducted show different exploratory exploitative behaviors FOX. employs solve engineering problems, such as pressure vessel design, it electrical power generation: economic load dispatch problems. has achieved terms optimizing problems GWO, PSO, WOA, FDO.