Bio-Inspired Meta-Heuristic Algorithms: Sea-Horse Optimizer

Optimization problems are problems that should identify the best solution to fulfill the constraints and max/min of the objective function. In general, metaheuristic algorithms, a community of natureinspired approaches with specialized stochastic operators, have developed to address these difficult challenges. The development of computing technology indirectly encourages the development of several new algorithms. There has been a significant increase from the discovery of new metaheuristic methods in recent years to get better optimizations for non-linear and complex problems. Metaheuristic algorithm has the characteristics of a simple and optimal approach. In addition, metaheuristic algorithms are also durable and self-organized. Metaheuristic algorithms are computational intelligence paradigms especially used for sophisticated solving optimization problems. This paper proposes a novel swarm intelligence-based metaheuristic called as sea-horse optimizer (SHO), which is inspired by the movement, predation and breeding behaviors of sea horses in nature. The SHO is a method that duplicates the life of a Sea Horse in the ocean when it moves, looks for prey and breeds.