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Safeguarded Reinforcement Learning for Dynamic Environments

Optimal Control Applications and Methods, Volume 47, Issue 6, Page 1543-1555, November/December 2026.
This paper uses a combination of Reinforcement Learning and Funnel Control to train a fast and safe controller for systems operating in changing environments. Furthermore, the presented formulation overcomes former limitations associated with the need for predefined reference trajectories.
Simon Gottschalk
wiley   +1 more source

Quantum Machine Learning for Hydrological Simulation: A Perspective on Emerging Opportunities and Challenges

WIREs Water, Volume 13, Issue 6, November/December 2026.
Conceptual framework of physics‐guided hybrid quantum–classical machine learning for hydrological simulation, highlighting the opportunities and limitations of quantum computing and its integration with classical machine learning and mass‐balance physics.
Vidya Samadi
wiley   +1 more source

A polynomially solvable case of unconstrained (-1,1)-quadratic fractional optimization

In this paper, we consider an unconstrained (-1,1)-quadratic fractional optimization in the following form: $\min_{x\in\{-1,1\}^n}~(x^TAx+α)/(x^TBx+β)$, where $A$ and $B$, given by their nonzero eigenvalues and associated eigenvectors, have ranks not ...
Xia, Yong, Yang, Meijia
core  

Spectral Bounds for Unconstrained (−1,1)-Quadratic Optimization Problems

European Journal of Operational Research, 2010
International audienceGiven an unconstrained quadratic optimization problem in the following form: (QP)min {xtQx|xЄ{-1,1}n}, with QЄ nxn, we present different methods for computing bounds on its optimal objective value.
Jose Urias de Moraes Neto
exaly   +2 more sources

An Efficient Closed-Form Formula for Evaluating r-Flip Moves in Quadratic Unconstrained Binary Optimization

Algorithms, 2023
Quadratic unconstrained binary optimization (QUBO) is a classic NP-hard problem with an enormous number of applications. Local search strategy (LSS) is one of the most fundamental algorithmic concepts and has been successfully applied to a wide range of ...
Bahram Alidaee, Lutfu S Sua, Haibo Wang
exaly   +2 more sources

The Unconstrained Binary Quadratic Programming Problem: A Survey [PDF]

Journal of Combinatorial Optimization, 2014
In recent years the unconstrained binary quadratic program (UBQP) has grown in importance in the field of combinatorial optimization due to its application potential and its computational challenge. Research on UBQP has generated a wide range of solution
Fred W. Glover, Jin-Kao Hao, Zhipeng Lu
exaly   +2 more sources

A Hybrid Metaheuristic for Multiobjective Unconstrained Binary Quadratic Programming [PDF]

Applied Soft Computing Journal, 2014
International audienceThe conventional Unconstrained Binary Quadratic Programming (UBQP) problem is known to be a unified modeling and solution framework for many combinatorial optimization problems.
Jin-Kao Hao, Sébastien Verel, Arnaud Liefooghe   +2 more
exaly   +2 more sources

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Digital Annealer for Quadratic Unconstrained Binary Optimization: A Comparative Performance Analysis

Applied Soft Computing Journal, 2022
Merve Bodur, Oylum Şeker
exaly  

Logical and Inequality Implications for Reducing the Size and Difficulty of Quadratic Unconstrained Binary Optimization Problems

European Journal of Operational Research, 2018
Fred W. Glover, Mark W. Lewis, Gary Kochenberger   +2 more
exaly  

How to Approximate Any Objective Function via Quadratic Unconstrained Binary Optimization

2022
Thomas Gabor, Claudia Linnhoff-Popien
exaly