Homotopy methods are powerful tools for solving nonlinear programming. Their global convergence can be generally established under conditions of the nonemptiness and boundness of the interior of the feasible set, the Positive Linear Independent Constraint Qualification (PLICQ), which is equivalent to the Mangasarian-Fromovitz Constraint Qualification (MFCQ), and the normal cone condition. This paper provides a comparison of the existing normal cone conditions used in homotopy methods for solving inequality constrained nonlinear programming
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
Several algorithms in optimization can be viewed as following a solution as a parameter or set of pa...
In this work, we address some advantages of Nonlinear Programming (NLP) based methods for inequality...
For many years, globally convergent probability-one homotopy methods have been remarkably succes...
Probability-one homotopy methods are a class of algorithms for solving nonlinear systems of equation...
In this note we give a new, simple proof of the standard first and second order necessary conditions...
In the paper, the aggregate constraint-shifting homotopy method for solving general nonconvex nonlin...
We consider constraint qualifications in nonlinear programming which can be reduced to the classical...
The paper concerns the computation of the limiting coderivative of the normal-cone mapping related t...
We present a new class of algorithms for determining whether there exists a point x ɛ Rn satisfying ...
The complexity of finding {Mathematical expression}-approximate first-order critical points for the ...
AbstractIn this paper, a constraint shifting combined homotopy method for solving multi-objective pr...
AbstractIn this paper, a new algorithm for tracing the combined homotopy path of the non-convex nonl...
Abstract. We study best approximation problems with nonlinear constraints in Hilbert spaces. The str...
In this note, we consider the solution of a linear program, using suitably adapted homotopy techniq...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
Several algorithms in optimization can be viewed as following a solution as a parameter or set of pa...
In this work, we address some advantages of Nonlinear Programming (NLP) based methods for inequality...
For many years, globally convergent probability-one homotopy methods have been remarkably succes...
Probability-one homotopy methods are a class of algorithms for solving nonlinear systems of equation...
In this note we give a new, simple proof of the standard first and second order necessary conditions...
In the paper, the aggregate constraint-shifting homotopy method for solving general nonconvex nonlin...
We consider constraint qualifications in nonlinear programming which can be reduced to the classical...
The paper concerns the computation of the limiting coderivative of the normal-cone mapping related t...
We present a new class of algorithms for determining whether there exists a point x ɛ Rn satisfying ...
The complexity of finding {Mathematical expression}-approximate first-order critical points for the ...
AbstractIn this paper, a constraint shifting combined homotopy method for solving multi-objective pr...
AbstractIn this paper, a new algorithm for tracing the combined homotopy path of the non-convex nonl...
Abstract. We study best approximation problems with nonlinear constraints in Hilbert spaces. The str...
In this note, we consider the solution of a linear program, using suitably adapted homotopy techniq...
AbstractIn this paper an algorithm for solving a linearly constrained nonlinear programming problem ...
Several algorithms in optimization can be viewed as following a solution as a parameter or set of pa...
In this work, we address some advantages of Nonlinear Programming (NLP) based methods for inequality...