Results 101 to 110 of about 1,804,722 (202)

Threshold Regression for Fixed‐T$$ T $$ Panel Data with Interactive Fixed Effects

open access: yesOxford Bulletin of Economics and Statistics, EarlyView.
ABSTRACT This paper develops a new toolbox for estimation and inference in panel data threshold regression models with interactive fixed effects and a fixed number of time periods, T$$ T $$. The toolbox is designed to be simple, accurate, and computationally efficient.
Jan Ditzen   +2 more
wiley   +1 more source

Surrogate‐Assisted Nonlinear Model Predictive Control for a Lambda Robot

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 26, Issue 4, December 2026.
ABSTRACT This work presents a nonlinear model predictive control (NMPC) framework for a lambda‐shaped parallel robot that incorporates data‐driven surrogates to facilitate control design. An inverse surrogate model is used to provide an efficient initialization of the control inputs for NMPC.
Sanam Hajipour   +2 more
wiley   +1 more source

Decomposition-Based Method for Sparse Semidefinite Relaxations of Polynomial Optimization Problems [PDF]

open access: yes
We consider polynomial optimization problems pervaded by a sparsity pattern. It has been shown in [1, 2] that the optimal solution of a polynomial programming problem with structured sparsity can be computed by solving a series of semidefinite ...
Berc Rustem   +2 more
core  

On convergence of the maximum block improvement method [PDF]

open access: yes, 2015
. The MBI (maximum block improvement) method is a greedy approach to solving optimization problems where the decision variables can be grouped into a finite number of blocks. Assuming that optimizing over one block of variables while fixing all others is
Shuzhong Zhang   +5 more
core   +1 more source

Multi-Objective Optimization Technique Based on QUBO and an Ising Machine

open access: yesIEEE Access
With an increase in the complexity of society, solving multi-objective optimization problems (MOPs) has become crucial. In this study, we introduced a novel method called “quadratic unconstrained binary optimization based on the weighted normal ...
Hiroshi Ikeda, Takashi Yamazaki
doaj   +1 more source

Optimizing Household Waste Recycling Centre Network Reorganization in Hampshire

open access: yesNetworks, Volume 88, Issue 3, Page 313-330, October 2026.
ABSTRACT Local councils across the UK are facing sustained financial pressures, and Household Waste Recycling Centres (HWRCs) are being increasingly considered for closure to reduce expenditure. In 2024, Hampshire County Council, which operates the largest HWRC network in the UK, proposed closing either five or twelve existing sites.
Montree Jaidee   +4 more
wiley   +1 more source

On Insurer Portfolio Optimization. An Underwriting Risk Model [PDF]

open access: yes
Multicriteria portfolio optimization started with the Markowitz mean-variance model (Markowitz 1952, 1959). This model assumes that the goal of an average or standard investor is to maximize the unknown return on investment.
Preda, Vasile, Ciumara, Roxana
core  

Exact solutions of some nonconvex quadratic optimization problems via SDP and SOCP relaxations

open access: yes, 2017
We show that SDP (semidefinite programming) and SOCP (second order cone programming) relaxations provide exact optimal solutions for a class of nonconvex quadratic optimization problems. It is a generalization of the results by S. Zhang for a subclass of
김선영
core   +1 more source

A Practical Tutorial on Physics‐Informed Networks for Pharmacometrics and Quantitative Systems Pharmacology

open access: yesCPT: Pharmacometrics &Systems Pharmacology, Volume 15, Issue 10, October 2026.
ABSTRACT Inverse problems in pharmacometrics and quantitative systems pharmacology (QSP) often involve sparse, noisy data, limited measurable states, and complex dynamical systems. Traditional parameter estimation methods can struggle with ill‐posed problems, stiffness, discontinuities, and gray‐box scenarios where only part of the system dynamics is ...
Nazanin Ahmadi Daryakenari   +1 more
wiley   +1 more source

Convex and nonconvex optimization geometries

open access: yes, 2019
Includes bibliographical references.2019 Summer.Many machine learning and signal processing problems are fundamentally nonconvex. One way to solve them is to transform them into convex optimization problems (a.k.a. convex relaxation), which constitutes a
Li, Qiuwei
core  

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