Solving large-scale multimodal optimization problems
Keywords:
мультимодальні оптимізаційні задачі; тестові задачі; метод точної квадратичної регуляризації.Abstract
This paper considers large-scale multimodal optimization problems. Such problems have many local extrema. These problems are quite difficult to solve with modern methods. But most practical optimization problems are multimodal. The libraries of test and applied multimodal problems have been developed to test the effectiveness of new methods of global optimization. There is a problem with how to determine the effectiveness of the method when solving the problems from these libraries. We propose a simple criterion for determining the effectiveness of the optimization method. It is proposed to consider only problems with unknown solutions. Then it is better to consider such a method that gives better solutions for a larger number of problems from these libraries. The paper shows that today the best method for solving large-scale multimodal problems is the method of exact quadratic regularization.
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