Displaying similar documents to “Two minimax-type methods for solving systems of nonlinear equations”

On a classification of stationary points in nonlinear programming

Jaroslav Hrouda (1969)

Aplikace matematiky

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In the paper the definition of the regular stationary point (M. Altman) is extended to be embracing all the points to which the method of feasible directions can converge if used without respect to the regularity condition.

First- and second-order optimality conditions for mathematical programs with vanishing constraints

Tim Hoheisel, Christian Kanzow (2007)

Applications of Mathematics

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We consider a special class of optimization problems that we call Mathematical Programs with Vanishing Constraints, MPVC for short, which serves as a unified framework for several applications in structural and topology optimization. Since an MPVC most often violates stronger standard constraint qualification, first-order necessary optimality conditions, weaker than the standard KKT-conditions, were recently investigated in depth. This paper enlarges the set of optimality criteria...

An algorithm for solving multiple objective integer linear programming problem

Moncef Abbas, Djamal Chaabane (2002)

RAIRO - Operations Research - Recherche Opérationnelle

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In the present paper a complete procedure for solving Multiple Objective Integer Linear Programming Problems is presented. The algorithm can be regarded as a corrected form and an alternative to the method that was proposed by Gupta and Malhotra. A numerical illustration is given to show that this latter can miss some efficient solutions. Whereas, the algorithm stated bellow determines all efficient solutions without missing any one.

An SQP method for mathematical programs with complementarity constraints with strong convergence properties

Matus Benko, Helmut Gfrerer (2016)

Kybernetika

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We propose an SQP algorithm for mathematical programs with complementarity constraints which solves at each iteration a quadratic program with linear complementarity constraints. We demonstrate how strongly M-stationary solutions of this quadratic program can be obtained by an active set method without using enumeration techniques. We show that all limit points of the sequence of iterates generated by our SQP method are at least M-stationary.