Efficient numerical solving of difficult multimodal problems
DOI:
https://doi.org/10.17721/2706-9699.2025.2.02Keywords:
global optimization, test functions, exact quadratic regularization method, coordinate descent method, computational experimentsAbstract
Most mathematical optimization models of the applied problems are multimodal. Many methods and algorithms have been developed and are being developed for their solution. To verify the effectiveness of such methods, many test functions and problems have been developed. But most of such test functions are simple. They are symmetric, of low dimension, and have known solutions. This complicates the verification of the effectiveness of existing and new methods of global optimization. The paper proposes modifications of known test functions that satisfy the efficiency conditions. The minima of these functions are found by the method of exact quadratic regularization. The results obtained are significantly better than the solutions obtained by other methods.
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