Globally Convergent Interior-Point Algorithm for Nonlinear Programming

This paper presents a primal-dual interior-point algorithm for solving general constrained nonlinear programming problems. The inequality constraints are incorporated into the objective function by means of a logarithmic barrier function. Also, satisfaction of the equality constraints is enforced th...

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Vydáno v:	Journal of optimization theory and applications Ročník 125; číslo 3; s. 497 - 521
Hlavní autoři:	Akrotirianakis, I., Rustem, B.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York, NY Springer 01.06.2005 Springer Nature B.V
Témata:	Algorithms Applied sciences Convergence Exact sciences and technology Inequalities Mathematical analysis Mathematical models Mathematical programming Nonlinear programming Operational research and scientific management Operational research. Management science Optimization Strategy Studies Logarithmic function Barrier function Primal-dual interior-point algorithms Interior point method Constraint satisfaction Non linear programming Adaptive method merit functions Penalty function Inequality constraint Equality constraint Primal dual method convergence theory Objective function Quadratic function
ISSN:	0022-3239, 1573-2878
On-line přístup:	Získat plný text
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