Displaying similar documents to “New results on semidefinite bounds for ℓ 1 -constrained nonconvex quadratic optimization”

Quadratic 0–1 programming: Tightening linear or quadratic convex reformulation by use of relaxations

Alain Billionnet, Sourour Elloumi, Marie-Christine Plateau (2008)

RAIRO - Operations Research

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Many combinatorial optimization problems can be formulated as the minimization of a 0–1 quadratic function subject to linear constraints. In this paper, we are interested in the exact solution of this problem through a two-phase general scheme. The first phase consists in reformulating the initial problem either into a compact mixed integer linear program or into a 0–1 quadratic convex program. The second phase simply consists in submitting the reformulated problem to a standard solver....

A novel kernel function bridging iteration bounds in interior-point algorithms for linear programming

Imene Touil, Sajad Fathi-Hafshejani (2025)

Kybernetika

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Kernel functions play an important role in designing and analyzing interior-point methods. They are not only used for determining search directions but also for measuring the distance between the given iterate and the μ -center in the algorithms. Currently, interior-point methods based on kernel functions are among the most effective methods for solving different types of optimization problems and are very active research area in mathematical programming. Therefore, in this work, we introduce...

Saddle points criteria via a second order η -approximation approach for nonlinear mathematical programming involving second order invex functions

Tadeusz Antczak (2011)

Kybernetika

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In this paper, by using the second order η -approximation method introduced by Antczak [3], new saddle point results are obtained for a nonlinear mathematical programming problem involving second order invex functions with respect to the same function η . Moreover, a second order η -saddle point and a second order η -Lagrange function are defined for the so-called second order η -approximated optimization problem constructed in this method. Then, the equivalence between an optimal solution...

Redinv-SA: la simulated annealing for the quadratic assignment problem

N. M.M. de Abreu, T. M. Querido, P. O. Boaventura-Netto (2010)

RAIRO - Operations Research

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An algebraic and combinatorial approach to the study of the Quadratic Assignment Problem produced theoretical results that can be applied to (meta) heuristics to give them information about the problem structure, allowing the construction of algorithms. In this paper those results were applied to inform a Simulated Annealing-type heuristic (which we called RedInv-SA). Some results from tests with known literature instances are presented.