Automatic design of metaheuristics: The future of optimization?

To discourage the inefficient manual invention and configuration of new metaheuristic optimization algorithms, a research team at IRIDIA, the artificial intelligence laboratory of the Université Libre de Bruxelles, studied the literature and outlined the strengths of automatic approaches to the design of metaheuristics, especially compared to the many redundant—and at times outlandish—metaphor-based metaheuristics.

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