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Physics-inspired graph neural networks (PI-GNNs) have been utilized as an efficient unsupervised framework for relaxing combinatorial optimization problems encoded through a specific graph structure and loss, reflecting dependencies between…

Machine Learning · Computer Science 2025-10-24 Martin Krutský , Gustav Šír , Vyacheslav Kungurtsev , Georgios Korpas

We analyze an adaptive boundary element method for the weakly-singular and hypersingular integral equations for the 2D and 3D Helmholtz problem. The proposed adaptive algorithm is steered by a residual error estimator and does not rely on…

Numerical Analysis · Mathematics 2019-03-21 Alex Bespalov , Timo Betcke , Alexander Haberl , Dirk Praetorius

In this paper, we propose a Bi-layer Predictionbased Reduction Branch (BP-RB) framework to speed up the process of finding a high-quality feasible solution for Mixed Integer Programming (MIP) problems. A graph convolutional network (GCN) is…

Optimization and Control · Mathematics 2022-09-28 Lingying Huang , Xiaomeng Chen , Wei Huo , Jiazheng Wang , Fan Zhang , Bo Bai , Ling Shi

This paper addresses the optimization of edge-weighted networks by maximizing algebraic connectivity to enhance network robustness. Motivated by the need for precise robot position estimation in cooperative localization and pose-graph…

Systems and Control · Electrical Eng. & Systems 2024-09-25 Neelkamal Somisetty , Harsha Nagarajan , Swaroop Darbha

Mixed-integer (MI) quadratic models subject to quadratic constraints, known as All-Quadratic MI Programs, constitute a challenging class of NP-complete optimization problems. The particular scenario of unbounded integers defines a subclass…

Optimization and Control · Mathematics 2025-09-16 Guy Zepko , Ofer M. Shir

We study ranked enumeration of join-query results according to very general orders defined by selective dioids. Our main contribution is a framework for ranked enumeration over a class of dynamic programming problems that generalizes…

Databases · Computer Science 2020-09-15 Nikolaos Tziavelis , Deepak Ajwani , Wolfgang Gatterbauer , Mirek Riedewald , Xiaofeng Yang

We present a new numerical algorithm for the solution of coupled collisional and collisionless systems, based on the block structured adaptive mesh and time refinement strategy (AMR). We describe the issues associated with the…

Astrophysics · Physics 2008-11-26 Francesco Miniati , Phillip Colella

We analyze the performance of the best-response dynamic across all normal-form games using a random games approach. The playing sequence -- the order in which players update their actions -- is essentially irrelevant in determining whether…

Theoretical Economics · Economics 2022-11-18 Torsten Heinrich , Yoojin Jang , Luca Mungo , Marco Pangallo , Alex Scott , Bassel Tarbush , Samuel Wiese

Motivated by emerging resource allocation and data placement problems such as web caches and peer-to-peer systems, we consider and study a class of resource allocation problems over a network of agents (nodes). In this model, nodes can…

Computer Science and Game Theory · Computer Science 2020-01-07 S. Rasoul Etesami

In this paper we develop a novel approach to the convergence of Best-Response Dynamics for the family of interference games. Interference games represent the fundamental resource allocation conflict between users of the radio spectrum. In…

Computer Science and Game Theory · Computer Science 2018-11-20 Ilai Bistritz , Amir Leshem

In this paper, we investigate distributed generalized Nash equilibrium (GNE) computation of monotone games with affine coupling constraints. Each player can only utilize its local objective function, local feasible set and a local block of…

Optimization and Control · Mathematics 2020-04-10 Peng Yi , Lacra Pavel

Information compression techniques are majorly employed to address the concern of reducing communication cost over peer-to-peer links. In this paper, we investigate distributed Nash equilibrium (NE) seeking problems in a class of…

Multiagent Systems · Computer Science 2023-09-22 Xiaomeng Chen , Yuchi Wu , Xinlei Yi , Minyi Huang , Ling Shi

Dynamic games are powerful tools to model multi-agent decision-making, yet computing Nash (generalized Nash) equilibria remains a central challenge in such settings. Complexity arises from tightly coupled optimality conditions, nested…

Computer Science and Game Theory · Computer Science 2026-02-06 Mahdis Rabbani , Navid Mojahed , Shima Nazari

We study the problem of computing an approximate Nash equilibrium of continuous-action game without access to gradients. Such game access is common in reinforcement learning settings, where the environment is typically treated as a black…

Computer Science and Game Theory · Computer Science 2023-08-30 Carlos Martin , Tuomas Sandholm

This paper examines the convergence behaviour of simultaneous best-response dynamics in random potential games. We provide a theoretical result showing that, for two-player games with sufficiently many actions, the dynamics converge quickly…

Computer Science and Game Theory · Computer Science 2025-05-19 Galit Ashkenazi-Golan , Domenico Mergoni Cecchelli , Edward Plumb

In this paper, we consider a continuous-type Bayesian Nash equilibrium (BNE) seeking problem in subnetwork zero-sum games, which is a generalization of deterministic subnetwork zero-sum games and discrete-type Bayesian zero-sum games. In…

Optimization and Control · Mathematics 2023-09-15 Hanzheng Zhang , Guanpu Chen , Yiguang Hong

This paper extends a new concept of energy-water-hydrogen (EWH) nexus, which was recently developed as a solution for reducing carbon emissions from the generation side of power systems, to the distribution side. Under the concept of…

Systems and Control · Electrical Eng. & Systems 2023-11-22 Mostafa Goodarzi , Qifeng Li

We address the generalized Nash equilibrium seeking problem for a population of agents playing aggregative games with affine coupling constraints. We focus on semi-decentralized communication architectures, where there is a central…

Optimization and Control · Mathematics 2022-06-16 Giuseppe Belgioioso , Sergio Grammatico

We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially displays a set of items to a population of customers and collects their choices as feedback.…

Machine Learning · Computer Science 2025-01-03 Junwen Yang , Yifan Feng

We formulate the optimal flow problem in a multi-area integrated electrical and gas system as a mixed-integer optimization problem by approximating the non-linear gas flows with piece-wise affine functions, thus resulting in a set of…

Optimization and Control · Mathematics 2022-09-13 Wicak Ananduta , Sergio Grammatico