Autor:	P. I. Stetsyuk, Naum Z. Shor
Rok vydání:	2002
Předmět:	Polynomial Mathematical optimization Control and Optimization Branch and bound L-reduction Applied Mathematics MathematicsofComputing_NUMERICALANALYSIS Management Science and Operations Research Computer Science Applications Nonlinear programming Quadratic equation Discrete optimization Quadratic programming Convex function Mathematics
Zdroj:	Journal of Global Optimization. 23:1-41
ISSN:	0925-5001
DOI:	10.1023/a:1014004625997
Popis:	Many polynomial and discrete optimization problems can be reduced to multiextremal quadratic type models of nonlinear programming. For solving these problems one may use Lagrangian bounds in combination with branch and bound techniques. The Lagrangian bounds may be improved for some important examples by adding in a model the so-called superfluous quadratic constraints which modify Lagrangian bounds. Problems of finding Lagrangian bounds as a rule can be reduced to minimization of nonsmooth convex functions and may be successively solved by modern methods of nondifferentiable optimization. This approach is illustrated by examples of solving polynomial-type problems and some discrete optimization problems on graphs.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::5595463823d7c57c144dee214682314c https://doi.org/10.1023/a:1014004625997 Zobrazit plný text záznamu Full text from SpringerLink