Results 51 to 60 of about 1,056,028 (181)
Mathematical and Computational Applications, 2021 We present a local trust region descent algorithm for unconstrained and convexly constrained multiobjective optimization problems. It is targeted at heterogeneous and expensive problems, i.e., problems that have at least one objective function that is ...
Manuel Berkemeier, Sebastian Peitz
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Derivative-Free Conformable Iterative Methods for Solving Nonlinear Equations
Fractal and Fractional, 2023 In this manuscript, we use approximations of conformable derivatives for designing iterative methods to solve nonlinear algebraic or trascendental equations. We adapt the approximation of conformable derivatives in order to design conformable derivative-free iterative schemes to solve nonlinear equations: Steffensen and Secant-type methods.
Giro Candelario +3 more
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, 2009 We investigate how the divergence-free property of magnetic fields can be exploited to resolve the azimuthal ambiguity present in solar vector magnetogram data, by using line-of-sight and horizontal heliographic derivative information as approximated ...
A. D. Crouch +33 more
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No Go Theorem for Self Tuning Solutions With Gauss-Bonnet Terms
, 2002 We consider self tuning solutions for a brane embedded in an anti de Sitter spacetime. We include the higher derivative Gauss-Bonnet terms in the action and study singularity free solutions with finite effective Newton's constant.
C. Charmousis +11 more
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Sequential Penalty Derivative-Free Methods for Nonlinear Constrained Optimization
SIAM Journal on Optimization, 2010 We consider the problem of minimizing a continuously differentiable function of several variables subject to smooth nonlinear constraints. We assume that the first order derivatives of the objective function and of the constraints can be neither calculated nor explicitly approximated.
LIUZZI, Giampaolo +2 more
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Model-Based Derivative-Free Methods for Convex-Constrained Optimization
SIAM Journal on Optimization, 2022 We present a model-based derivative-free method for optimization subject to general convex constraints, which we assume are unrelaxable and accessed only through a projection operator that is cheap to evaluate. We prove global convergence and a worst-case complexity of $O(ε^{-2})$ iterations and objective evaluations for nonconvex functions, matching ...
Matthew Hough, Lindon Roberts
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Derivative Formula and Applications for Hyperdissipative Stochastic Navier-Stokes/Burgers Equations [PDF]
, 2010 By using coupling method, a Bismut type derivative formula is established for the Markov semigroup associated to a class of hyperdissipative stochastic Navier-Stokes/Burgers equations.
Wang, Feng-Yu, Xu, Lihu
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, 2017 Defects such as dislocations impact materials properties and their response during external stimuli. Defect engineering has emerged as a possible route to improving the performance of materials over a wide range of applications, including batteries ...
Menickelly, M. +2 more
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, 2016 We implemented the derivative of the free energy functional with respect to the atom displacements, so called force, within the combination of Density Functional Theory and the Embedded Dynamical Mean Field Theory.
Haule, Kristjan, Pascut, Gheorghe L.
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A Second-Order Finite-Difference Method for Derivative-Free Optimization
Journal of MathematicsIn this paper, a second-order finite-difference method is proposed for finding the second-order stationary point of derivative-free nonconvex unconstrained optimization problems.
Qian Chen, Peng Wang, Detong Zhu
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