S. Lucid

In this paper we propose a primal-dual algorithm for the solution of general nonlinear programming problems. The core of the method is a local algorithm which relies on a truncated procedure for the computation of a search direction, and is thus suitable for large scale problems. The truncated direction produces a sequence of points which locally converges to a KKT

In this paper we introduce a Newton-type algorithm model for solving smooth nonlinear optimization problems with general constraints and bound constraints on the variables. Under very mild assumptions and without requiring the strict complementarity assumption, thc algorithm produces a sequence of pairs {(x , λ )} converging quadratically to , where is the solution of the problem and is the

Mixed-Integer optimization represents a powerful tool for modeling manyoptimization problems arising from real-world applications. The Feasibilitypump is a heuristic for finding feasible solutions to mixed integer linear problems. In this work, we propose a new feasibility pump approach using concave nondifferentiable penalty functions for measuring solution integrality. We present computational results on binary MILP problems from the MIPLIB library showing the effectiveness of our approach.

Mixed-Integer optimization is a powerful tool for modeling many optimization problems arising from real-world applications. Finding a rst feasible solution represents the rst step for several MIP solvers. The Feasibility pump is a heuristic for nding feasible solutions to mixed integer linear problems which is eective even when dealing with hard MIP instances. In this work, we start by interpreting

In this paper we aim at carrying out and describing some issues for real eigen-value computation via iterative methods. More specifically we work out new techniques for iteratively developing specific tridiagonalizations of a symmet-ric and indefinite matrix AG IRÒ¢Ò, by means of ...

Mixed-Integer optimization represents a powerful tool for modelling many optimization problems arising from real-world applications. The Feasibility pump is a heuristic for finding feasible solutions to mixedinteger linear problems. In this work, we propose a new feasibility pump approach for MIP problems using concave non differentiable penalty functions for measuring solution integrality.