Results 41 to 50 of about 146 (138)
Nonsmooth spectral gradient methods for unconstrained optimization
To solve nonsmooth unconstrained minimization problems, we combine the spectral choice of step length with two well-established subdifferential-type schemes: the gradient sampling method and the simplex gradient method.
Milagros Loreto +3 more
doaj +1 more source
Some properties of approximate solutions for vector optimization problem with set-valued functions
Vector optimization, Set-valued function, Scalarization, Approximate solution, Quasiconvex set-valued function, 90C26, 90C29, 90C59,
Qiusheng Qiu, Xinmin Yang
core +1 more source
On global optimization with indefinite quadratics
We present an algorithmic framework for global optimization problems in which the non-convexity is manifested as an indefinite-quadratic as part of the objective function.
Marcia Fampa, Jon Lee, Wendel Melo
doaj +1 more source
Hybrid conjugate gradient-BFGS methods based on Wolfe line search
In this paper, we present some hybrid methods for solving unconstrained optimization problems. These methods are defined using proper combinations of the search directions and included parameters in conjugate gradient and quasi-Newton method of Broyden ...
DJAMEL, Benterki, SAMIA, Khelladi
core +1 more source
Generalized McCormick relaxations
Convex relaxations, Global optimization, Optimal control, 49M20, 90C26,
Joseph Scott +2 more
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
core +1 more source
Data envelopment analysis, free disposal hull, technical efficiency, 90B30, 90B50, 90C26,
Kristiaan Kerstens, Walter Briec
core +1 more source
Sensitivity analysis of a continuous multifacility competitive location and design problem
Continuous location, Facility design, Competition, Multifacility, Sensitivity analysis, Evolutionary algorithm, Computational study, 90B85, 90C31, 90C26, 68T20,
P. Ortigosa +5 more
core +1 more source
Refined optimality conditions for differences of convex functions
Diff-convex, Optimality, 90C26, 90C46,
Tuomo Valkonen
core +1 more source
On a theorem due to Crouzeix and Ferland
Nonsmooth analysis, Nonsmooth optimization, Generalized convexity, KT pseudoconvex problems, FJ pseudoconvex problems, Quasiconvex programming, 90C26, 26B25, 49J52,
Vsevolod Ivanov
core +1 more source

