Algorithm Selection: From Meta-Learning to Hyper-Heuristics

In order for a company to be competitive, an indispensable requirement is the efficient management of its resources. As a result derives a lot of complex optimization problems that need to be solved with high-performance computing tools. In addition, due to the complexity of these problems, it is considered that the most promising approach is the solution with approximate algorithms; highlighting the heuristic optimizers. Within this category are the basic heuristics that are experience-based techniques and the metaheuristic algorithms that are inspired by natural or artificial optimization processes.

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