HOGO: Hide Objects Game Optimization

A number of metaphysical algorithms have been developed in recent years.Most of these algorithms are inspired by physical processes or living beings' behaviour.In this paper, a new algorithm namely "Hide Objects Game Optimization (HOGO)" is presented to obtain quasi-optimal solution.It is inspired by an old game and the searcher agents who try to find a hidden object in a given space.In this game, any player must notice the following points: (a) pay attention to the voices made by the coach for players, (b) get closer to the best player for whom the coach made the loudest voice, (c) take influence from the voices made by the coach for other players, (d) compare the new voice after a move with the old voice before the move and return back in case the voice gets lower.HOGO is tested on 23 well-known benchmark test functions and is compared with eight optimization algorithms: Genetic Algorithm, Particle Swarm Optimization, Gravitational Search Algorithm, Teaching Learning Based Optimization, Grey Wolf Optimizer, Grasshopper Optimization Algorithm, Spotted Hyena Optimizer, and Emperor Penguin Optimizer.The results and data obtained from applying HOGO and other said algorithms show that HOGO is able to provide better results in comparison with other well-known optimization algorithms.