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We study some optimal control problems associated to the evolution of two isothermal, incompressible, immisible fluids in a two-dimensional bounded domain. The Cahn- Hilliard-Navier-Stokes model consists of a Navier-Stokes equation…

Analysis of PDEs · Mathematics 2019-03-20 Tania Biswas , Sheetal Dharmatti , Manil T Mohan

Abstract approaches to maximum and anti-maximum principles for differential operators typically rely on the condition that all vectors in the domain of the operator are dominated by the leading eigenfunction of the operator. We study the…

Analysis of PDEs · Mathematics 2024-04-12 Sahiba Arora , Jochen Glück

We consider the minimum weight and smallest weight minimum-size dominating set problems in vertex-weighted graphs and networks. The latter problem is a two-objective optimization problem, which is different from the classic minimum weight…

Combinatorics · Mathematics 2024-01-23 Lukas Dijkstra , Andrei Gagarin , Vadim Zverovich

We consider optimal control problems, where the control appears in the main part of the operator. We derive the Pontryagin maximum principle as a necessary optimality condition. The proof uses the concept of topological derivatives. In…

Optimization and Control · Mathematics 2024-08-01 Daniel Wachsmuth

In a recent paper by two of the authors, the concepts of upwards and downwards $\epsilon$-movability were introduced, mainly as a technical tool for studying dynamical percolation of interacting particle systems. In this paper, we further…

Probability · Mathematics 2007-05-23 Erik I. Broman , Olle Haggstrom , Jeffrey E. Steif

Model-free reinforcement learning methods lack an inherent mechanism to impose behavioural constraints on the trained policies. Although certain extensions exist, they remain limited to specific types of constraints, such as value…

Machine Learning · Computer Science 2025-04-28 Bram De Cooman , Johan Suykens

This paper considers mathematical programs, whose constraints are expressed by a parameterized vector equilibrium problem. The latter is a well recognized framework, which is able to cover multicriteria optimization, vector variational…

Optimization and Control · Mathematics 2022-10-18 Amos Uderzo

This paper explores some sufficient conditions for the enhanced solvability of strong vector equilibrium problems, which can be established via a variational approach. Enhanced solvability here means existence of solutions, which are strong…

Optimization and Control · Mathematics 2022-05-11 Amos Uderzo

A general maximum principle is proved for optimal controls of abstract semilinear stochastic evolution equations. The control variable, as well as linear unbounded operators, acts in both drift and diffusion terms, and the control set need…

Optimization and Control · Mathematics 2013-12-30 Kai Du , Qingxin Meng

This work addresses the optimal birth control problem for invasive species in a spatial environment. We apply the method of semigroups to qualitatively analyze a size-structured population model in which individuals occupy a position in a…

Optimization and Control · Mathematics 2021-04-12 Manoj Kumar , Syed Abbas

This paper focuses on Bayesian Optimization in combinatorial spaces. In many applications in the natural science. Broad applications include the study of molecules, proteins, DNA, device structures and quantum circuit designs, a on…

Machine Learning · Computer Science 2020-11-13 Tony C. Wu , Daniel Flam-Shepherd , Alán Aspuru-Guzik

Numerous machine learning problems require an exploration basis - a mechanism to explore the action space. We define a novel geometric notion of exploration basis with low variance, called volumetric spanners, and give efficient algorithms…

Machine Learning · Computer Science 2014-05-27 Elad Hazan , Zohar Karnin , Raghu Mehka

Generalized polyhedral convex optimization problems in locally convex Hausdorff topological vector spaces are studied systematically in this paper. We establish solution existence theorems, necessary and sufficient optimality conditions,…

Optimization and Control · Mathematics 2017-10-02 Nguyen Ngoc Luan , Jen-Chih Yao

This survey is focused on certain sequential decision-making problems that involve optimizing over probability functions. We discuss the relevance of these problems for learning and control. The survey is organized around a framework that…

Optimization and Control · Mathematics 2023-01-13 Emiland Garrabe , Giovanni Russo

Distributed optimization algorithms are used in a wide variety of problems involving complex network systems where the goal is for a set of agents in the network to solve a network-wide optimization problem via distributed update rules. In…

Optimization and Control · Mathematics 2025-09-23 Liam Hallinan , Ioannis Lestas

It is an attractive hypothesis that the spatial structure of visual cortical architecture can be explained by the coordinated optimization of multiple visual cortical maps representing orientation preference (OP), ocular dominance (OD),…

Neurons and Cognition · Quantitative Biology 2015-06-03 Lars Reichl , Dominik Heide , Siegrid Löwel , Justin C. Crowley , Matthias Kaschube , Fred Wolf

Controllability and observability have long been recognized as fundamental structural properties of dynamical systems, but have recently seen renewed interest in the context of large, complex networks of dynamical systems. A basic problem…

Optimization and Control · Mathematics 2016-11-18 Tyler H. Summers , Fabrizio L. Cortesi , John Lygeros

We consider the Maximum Vectors problem in a strategic setting. In the classical setting this problem consists, given a set of $k$-dimensional vectors, in computing the set of all nondominated vectors. Recall that a vector $v=(v^1, v^2,…

Computer Science and Game Theory · Computer Science 2019-03-26 Eric Angel , Evripidis Bampis

In this paper, we consider the optimal control problem for a class of evolution inclusions with Volterra type operators, which can be history-dependent. We establish the existence of a solution to the stated optimal control problem under…

Analysis of PDEs · Mathematics 2021-05-19 M. Bokalo , O. Sus

In all but the most trivial optimization problems, the structure of the solutions exhibit complex interdependencies between the input parameters. Decades of research with stochastic search techniques has shown the benefit of explicitly…

Neural and Evolutionary Computing · Computer Science 2017-03-23 Shumeet Baluja