Due to abundance of novel optimization algorithms in recent years, the problem of large similarities among methods that are named differently is becoming troublesome and general. The question arises if the novel source of inspiration is sufficient to breed an optimization algorithm with a novel name, even if its search properties are almost the same as, or are even a simplified variant of, the search properties of an older and well-known method. In this paper it is rigidly shown that the recently proposed heuristic approach called the black hole optimization is in fact a simplified version of Particle Swarm Optimization with inertia weight. Additionally, because a large number of metaheuristics developed during the last decade is claimed to be nature-inspired, a short discussion on inspirations of optimization algorithms is presented.
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