A short review on novel approaches for maximum clique problem: from classical algorithms to graph neural networks and quantum algorithms

R Marino, L Buffoni, B Zavalnij - arxiv preprint arxiv:2403.09742, 2024 - arxiv.org
This manuscript provides a comprehensive review of the Maximum Clique Problem, a
computational problem that involves finding subsets of vertices in a graph that are all …

Fuzzy Self-tuning Bees Algorithm for designing optimal product lines

K Zervoudakis, S Tsafarakis - Applied Soft Computing, 2024 - Elsevier
Abstract The Product Line Design (PLD) problem is an NP-hard combinatorial optimization
problem in marketing that aims at determining an optimal product line through which a firm …

Frequent pattern-based search: A case study on the quadratic assignment problem

Y Zhou, JK Hao, B Duval - IEEE Transactions on Systems, Man …, 2020 - ieeexplore.ieee.org
We present frequent pattern-based search (FPBS) that combines data mining and
optimization. FPBS is a general-purpose method that unifies data mining and optimization …

Lense: Learning to navigate subgraph embeddings for large-scale combinatorial optimisation

D Ireland, G Montana - International conference on machine …, 2022 - proceedings.mlr.press
Combinatorial Optimisation problems arise in several application domains and are often
formulated in terms of graphs. Many of these problems are NP-hard, but exact solutions are …

Metaheuristic-based hyperparameter optimization for multi-disease detection and diagnosis in machine learning

J Singh, JK Sandhu, Y Kumar - Service Oriented Computing and …, 2024 - Springer
Metaheuristic algorithms with machine learning techniques have become popular because it
works so well for problems like regression, classification, rule mining, and clustering in …

COMBHelper: A Neural Approach to Reduce Search Space for Graph Combinatorial Problems

H Tian, S Medya, W Ye - Proceedings of the AAAI Conference on …, 2024 - ojs.aaai.org
Combinatorial Optimization (CO) problems over graphs appear routinely in many
applications such as in optimizing traffic, viral marketing in social networks, and matching for …

Geometric deep learning sub-network extraction for maximum clique enumeration

V Carchiolo, M Grassia, M Malgeri, G Mangioni - Plos one, 2024 - journals.plos.org
The paper presents an algorithm to approach the problem of Maximum Clique Enumeration,
a well known NP-hard problem that have several real world applications. The proposed …

[HTML][HTML] Using Machine Learning in Combinatorial Optimization: Extraction of Graph Features for Travelling Salesman Problem

P Stodola, R Ščurek - Knowledge-Based Systems, 2025 - Elsevier
Abstract Machine learning has emerged as a paradigmatic approach for addressing
complex problems across various scientific disciplines, including combinatorial optimization …

Open problems in (hyper) graph decomposition

D Ajwani, RH Bisseling, K Casel, ÜV Çatalyürek… - arxiv preprint arxiv …, 2023 - arxiv.org
Large networks are useful in a wide range of applications. Sometimes problem instances
are composed of billions of entities. Decomposing and analyzing these structures helps us …

Theoretically Grounded Pruning of Large Ground Sets for Constrained, Discrete Optimization

A Nath, A Kuhnle - arxiv preprint arxiv:2410.17945, 2024 - arxiv.org
Modern instances of combinatorial optimization problems often exhibit billion-scale ground
sets, which have many uninformative or redundant elements. In this work, we develop light …