Over the last decade, several metaheuristic algorithms have emerged to solve numerical function optimization problems. Since the performance of these algorithms presents a suboptimal behavior, a large number of studies have been carried out to find new and better algorithms. Therefore, this paper proposes a new metaheuristic algorithm, namely the car tracking optimization algorithm; it is inspired by observing the programming methods of other metaheuristic algorithms. And the proposed algorithm has been tested over 55 benchmark functions, and the results have been compared with firefly algorithm (FA), cuckoo searching algorithm (CS), and vortex search algorithm (VS). The results indicate that the performance of the proposed algorithm surpasses FA, CS, and VS algorithm.
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Conflict of interest
The authors declared that they have no conflicts of interest to this work.
This article does not contain any studies with human participants performed by any of the authors.
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