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On generating nonconvex optimization test problems

Авторы: Barkova M.

Журнал: Lecture Notes in Computer Science: Proc. of the 18th Intern. Conf. on Mathematical Optimization Theory and Operations Research (MOTOR'2019, Ekaterinburg)

Том: 11548 LNCS

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Год: 2019

Отчётный год: 2019

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Аннотация: This paper addresses a technique for generating two types of nonconvex test problems. We study quadratic problems with d.c. inequality constraints and sum-of-ratios programs where both numerators and denominators are quadratic functions. Based on the idea of P. Calamai and L. Vicente, we propose the procedures for constructing nonconvex test problems with quadratic functions of any dimension, where global and local solutions are known. The implementation of the procedures does not require any complicated operations and solving auxiliary problems, except for elementary operations with matrices and vectors.

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