The Space Decomposition Theory for a Class of Semi-Infinite Maximum Eigenvalue Optimizations
We study optimization problems involving eigenvalues of symmetric matrices. We present a nonsmooth optimization technique for a class of nonsmooth functions which are semi-infinite maxima of eigenvalue functions.
Ming Huang +3 more
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Abadie Type Constraint Qualifications and Optimality Conditions for Nonsmooth Multi-Objective Semi-Infinite Problems [PDF]
This paper introduces several Abadie-type constraint qualifications and derives necessary optimality conditions in the Karush-Kuhn-Tucker for both weakly efficient solutions and efficient solutions of a nonsmooth multi-objective semi-infinite programming
Ahmad Rezaee
doaj +1 more source
Second-order optimality conditions for interval-valued functions
This work is included in the search of optimality conditions for solutions to the scalar interval optimization problem, both constrained and unconstrained, by means of second-order optimality conditions.
Gabriel Ruiz-Garzón +3 more
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Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif +17 more
wiley +1 more source
In this paper, we examine a semi-infinite interval-valued optimization problem with vanishing constraints (SIVOPVC) that lacks differentiability and involves constraints that tend to vanish.
Bhuwan Chandra Joshi +2 more
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Optimality Conditions for Properly Efficient Solutions of Nonsmooth Multiobjective GSIP [PDF]
This paper aims to establish first-order necessary optimality conditions for non-smooth multi-objective generalized semi-infinite programming problems. These problems involve inequality constraints whose index set depends on the decision vector, and all ...
Ali Asghar Hojatifard +2 more
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A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
Numerical experiments in semi-infinite programming [PDF]
A quasi-Newton algorithm for semi-infinite programming using an L∞ exact penalty function is described, and numerical results are presented. Comparisons with three Newton algorithms and one other quasi-Newton algorithm show that the algorithm is very
Coope, I. D., Price, Christopher John
core
Post-optimal analysis in linear semi-infinite optimization
Post-Optimal Analysis in Linear Semi-Infinite Optimization examines the following topics in regards to linear semi-infinite optimization: modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis ...
López, Marco A, Goberna, Miguel A
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First-order optimality conditions for two classes of generalized nonsmooth semi-infinite optimization [PDF]
We investigate two classes of generalized nonsmooth semi-infinite optimization problems in this paper, that is, the generalized convex semi-infinite optimization problem and the generalized Lipscitz semi-infinite optimization problem.
Pang, Li-Ping +2 more
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