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The graph theoretic concept of maximal independent set arises in several practical problems in computer science as well as in game theory. A maximal independent set is defined by the set of occupied nodes that satisfy some packing and…

Disordered Systems and Neural Networks · Physics 2010-01-28 L. Dall'Asta , P. Pin , A. Ramezanpour

Many existing branch and bound algorithms for multiobjective optimization problems require a significant computational cost to approximate the entire Pareto optimal solution set. In this paper, we propose a new branch and bound algorithm…

Optimization and Control · Mathematics 2024-05-20 Weitian Wu , Xinmin Yang

Branch and bound methods which are based on the principle "divide and conquer" are a well established solution approach in single-objective integer programming. In multi-objective optimization branch and bound algorithms are increasingly…

Optimization and Control · Mathematics 2024-01-08 Julius Bauß , Sophie N. Parragh , Michael Stiglmayr

We introduce a new framework for reconfiguration problems, and apply it to independent sets as the first example. Suppose that we are given an independent set $I_0$ of a graph $G$, and an integer $l \ge 0$ which represents a lower bound on…

Discrete Mathematics · Computer Science 2018-04-26 Takehiro Ito , Haruka Mizuta , Naomi Nishimura , Akira Suzuki

Graphs are a natural representation of data from various contexts, such as social connections, the web, road networks, and many more. In the last decades, many of these networks have become enormous, requiring efficient algorithms to cut…

Data Structures and Algorithms · Computer Science 2021-08-11 Alexander Noe

The maximum independent set problem is a classic optimization problem that has also been studied quite intensively in the distributed setting. While the problem is hard to approximate in general, there are good approximation algorithms…

Data Structures and Algorithms · Computer Science 2025-06-13 Salwa Faour , Fabian Kuhn

The success of machine learning solutions for reasoning about discrete structures has brought attention to its adoption within combinatorial optimization algorithms. Such approaches generally rely on supervised learning by leveraging…

Machine Learning · Computer Science 2022-03-17 Ismail R. Alkhouri , George K. Atia , Alvaro Velasquez

The use of machine learning techniques to improve the performance of branch-and-bound optimization algorithms is a very active area in the context of mixed integer linear problems, but little has been done for non-linear optimization. To…

The Maximum Cut (Max-Cut) problem could be naturally expressed either in a Quadratic Unconstrained Binary Optimization (QUBO) formulation, or as an Ising model. It has long been known that the Maximum Independent Set (MIS) problem could…

Quantum Physics · Physics 2024-09-19 Chuixiong Wu , Jianan Wang , Fen Zuo

Given an edge-weighted graph $G$ on $n$ nodes, the NP-hard Max-Cut problem asks for a node bipartition such that the sum of edge weights joining the different partitions is maximized. We propose a fixed-parameter tractable algorithm…

Data Structures and Algorithms · Computer Science 2020-07-23 Markus Chimani , Christine Dahn , Martina Juhnke-Kubitzke , Nils M. Kriege , Petra Mutzel , Alexander Nover

Optimal control problems including partial differential equation (PDE) as well as integer constraints merge the combinatorial difficulties of integer programming and the challenges related to large-scale systems resulting from discretized…

Numerical Analysis · Mathematics 2021-09-09 Dominik Garmatter , Margherita Porcelli , Francesco Rinaldi , Martin Stoll

Machine learning is increasingly used to guide branch-and-cut (B&C) for mixed-integer linear programming by learning score-based policies for selecting branching variables and cutting planes. Many approaches train on local signals from…

Optimization and Control · Mathematics 2026-02-02 Hongyu Cheng , Amitabh Basu

The $k$-defective clique model relaxes the strict completeness constraint of the traditional clique by allowing up to $k$ missing edges, providing a robust formulation for detecting cohesive structures in noisy graphs. Consequently, the…

Databases · Computer Science 2026-05-19 Kewu Yang , Kaiqiang Yu , Shengxin Liu , Zhaoquan Gu

An instance of the Connected Maximum Cut problem consists of an undirected graph G = (V, E) and the goal is to find a subset of vertices S $\subseteq$ V that maximizes the number of edges in the cut \delta(S) such that the induced graph…

Data Structures and Algorithms · Computer Science 2015-07-03 MohammadTaghi Hajiaghayi , Guy Kortsarz , Robert MacDavid , Manish Purohit , Kanthi Sarpatwar

We consider the constrained graph alignment problem which has applications in biological network analysis. Given two input graphs $G_1=(V_1,E_1), G_2=(V_2,E_2)$, a pair of vertex mappings induces an {\it edge conservation} if the vertex…

Data Structures and Algorithms · Computer Science 2023-06-22 Ferhat Alkan , Türker Bıyıkoğlu , Marc Demange , Cesim Erten

The Maximum Balanced Subgraph Problem (MBSP) is the problem of finding a subgraph of a signed graph that is balanced and maximizes the cardinality of its vertex set. We are interested in the exact solution of the problem: an improved…

Discrete Mathematics · Computer Science 2013-12-17 Rosa Figueiredo , Yuri Frota

We initiate the study of deterministic distributed graph algorithms with predictions in synchronous message passing systems. The process at each node in the graph is given a prediction, which is some extra information about the problem…

Distributed, Parallel, and Cluster Computing · Computer Science 2026-01-01 Joan Boyar , Faith Ellen , Kim S. Larsen

The maximal biclique enumeration problem in bipartite graphs is fundamental and has numerous applications in E-commerce and transaction networks. Most existing studies adopt a branch-and-bound framework, which recursively expands a partial…

Data Structures and Algorithms · Computer Science 2026-02-26 Kaixin Wang , Kaiqiang Yu , Cheng Long

We give a combinatorial condition for the existence of efficient, LP-based FPT algorithms for a broad class of graph-theoretical optimisation problems. Our condition is based on the notion of biased graphs known from matroid theory.…

Data Structures and Algorithms · Computer Science 2020-02-21 Euiwoong Lee , Magnus Wahlström

We design improved approximation algorithms for NP-hard graph problems by incorporating predictions (e.g., learned from past data). Our prediction model builds upon and extends the $\varepsilon$-prediction framework by Cohen-Addad, d'Orsi,…

Machine Learning · Computer Science 2025-06-02 Anders Aamand , Justin Y. Chen , Siddharth Gollapudi , Sandeep Silwal , Hao Wu
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