Results 171 to 180 of about 1,963,970 (223)

Discrete Gradient Method: Derivative-Free Method for Nonsmooth Optimization [PDF]

Journal of Optimization Theory and Applications, 2008
A new derivative-free method is developed for solving unconstrained nonsmooth optimization problems. This method is based on the notion of a discrete gradient.
Bulent Karasözen, Adil M. Bagirov
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Necessary Conditions in Nonsmooth Optimization

Mathematics of Operations Research, 1984
The paper contains four theorems concerning first order necessary conditions for a minimum in nonsmooth optimization problems in Banach spaces: a Lagrange multiplier rule for a mathematical programming problem in which an infinite dimensional equality constraint is included in the constraints, a general maximum principle for nonsmooth optimal control ...
A D Ioffe
exaly   +4 more sources

Nonsmooth variational-like inequalities and nonsmooth vector optimization

Optimization Letters, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mohammad Alshahrani 0001, Qamrul Hasan Ansari, Suliman Al-Homidan   +2 more
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Nonsmooth Optimization and Robust Control [PDF]

Annual Reviews in Control, 2007
Many questions of robust control analysis and synthesis fundamentally involve nonsmooth sets and functions, and their variational properties. Central examples include distances to instability and uncontrollability, the H 1 norm, and pseudospectra.
exaly   +3 more sources

Nonsmooth optimization: theory and algorithms

4OR, 2009
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On Sufficient Conditions in Nonsmooth Optimization

Mathematics of Operations Research, 1982
Second-order conditions are given which are sufficient for a point to be a local minimizer for certain nonlinear programming problems defined on Banach spaces. The functions involved in the problems are not required to be smooth or convex; indeed, they are required only to satisfy certain conditions which are weak enough to be satisfied by all locally
openaire   +3 more sources

On Mixed Integer Nonsmooth Optimization

2020
In this chapter we review some deterministic solution methods for convex mixed integer nonsmooth optimization problems. The methods are branch and bound, outer approximation, extended cutting plane, extended supporting hyperplane and extended level bundle method.
Westerlund Karl, Mäkelä Marko, Eronen Ville-Pekka, Westerlund Tapio   +3 more
openaire   +1 more source

A New Nonsmooth Optimization Algorithm for Minimum Sum-of-Squares Clustering Problems

European Journal of Operational Research, 2006
The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed.
John Yearwood, Adil M. Bagirov
exaly   +1 more source

On Minimizing and Critical Sequences in Nonsmooth Optimization

SIAM Journal on Optimization, 2000
Let f be a bounded below, lower semicontinuous function from a Banach space into $R\cup \{+\infty \}.$ We study the relationships between minimizing and critical sequences of f, where the criticality condition is given in terms of some subdifferential $\partial.$ Here the objective function f is not supposed to be convex or smooth.
L. R. Huang, K. F. Ng, J. P. Penot
openaire   +2 more sources