Results 61 to 70 of about 162 (141)
A new augmented Lagrangian approach to duality and exact penalization
Augmented Lagrangian, Augmenting function, Nonconvex problem, Duality, 90C26, 90C46,
C. Lalitha
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Generalized derivatives and nonsmooth optimization, a finite dimensional tour
, 2005 Convex optimization, nonsmooth analysis, nonsmooth optimization, set-valued maps, variational analysis, mathematical programming, nonconvex programming, nonlinear programming, optimality conditions, second order conditions, tangent cones, normal cones ...
Joydeep Dutta
core +1 more source
P-algorithm based on a simplicial statistical model of multimodal functions
Statistical models of multimodal functions, Global optimization, Simplicial partition, 90C26,
Antanas Žilinskas, Julius Žilinskas
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Computing Integral Solutions of Complementarity Problems [PDF]
AMS classifications: 90C33, 90C26, 91B50.Discrete set;complementarity problem;algorithm ...
Laan, G. van der +2 more
core
Remarks on strict efficiency in scalar and vector optimization
Scalar optimization, Vector optimization, Strict efficiency, Basic subdifferential, Fréchet subdifferential, 90C29, 90C26, 49J52,
M. Durea
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Dai–Liao-type Riemannian optimization for solving the Gough–Stewart platform
EURO Journal on Computational OptimizationWe introduce a class of Dai–Liao-type Riemannian conjugate gradient (CG) methods that achieve global convergence without relying on the Gauss lemma, typically invoked under strong convexity assumptions.
Nasiru Salihu +3 more
doaj +1 more source
Piece adding technique for convex maximization problems
Global search algorithm, Local search algorithm, Nonconvex optimization, Convex maximization, Piecewise convex maximization, 90C26, 90C47, 49M05, 49M30,
Ider Tseveendorj, Dominique Fortin
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Central axes and peripheral points in high dimensional directional datasets.
, 2015 International audienceWe introduce a new notion of central axis for a finite set {a 1 ,. .. , a m } of vectors in R n. In tandem, we discuss different ways of measuring the dispersion of the data points a i 's around the central axis. Finally, we explain
Seeger, Alberto +2 more
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Journal of Inequalities and Applications, 2011 In this paper, an efficient modified nonlinear conjugate gradient method for solving unconstrained optimization problems is proposed. An attractive property of the modified method is that the generated direction in each step is always descending without ...
Liu Jinkui, Wang Shaoheng
doaj
Consensus-based optimisation with truncated noise
European Journal of Applied MathematicsConsensus-based optimisation (CBO) is a versatile multi-particle metaheuristic optimisation method suitable for performing non-convex and non-smooth global optimisations in high dimensions.
Massimo Fornasier +3 more
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