A method for urban air mobility network design using hub location and subgraph isomorphism
Rising concerns related to the effects of traffic congestion have led to the proposal of many
alternative solutions, including the idea of Urban Air Mobility (UAM), which uses electric …
alternative solutions, including the idea of Urban Air Mobility (UAM), which uses electric …
A new combinatorial branch-and-bound algorithm for the knapsack problem with conflicts
Abstract We study the Knapsack Problem with Conflicts, a generalization of the Knapsack
Problem in which a set of conflicts specifies pairs of items which cannot be simultaneously …
Problem in which a set of conflicts specifies pairs of items which cannot be simultaneously …
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms
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 …
computational problem that involves finding subsets of vertices in a graph that are all …
A branch-and-cut algorithm for the edge interdiction clique problem
Given a graph G and an interdiction budget k∈ N, the Edge Interdiction Clique Problem
(EICP) asks to find a subset of at most k edges to remove from G so that the size of the …
(EICP) asks to find a subset of at most k edges to remove from G so that the size of the …
[HTML][HTML] CliSAT: A new exact algorithm for hard maximum clique problems
Given a graph, the maximum clique problem (MCP) asks for determining a complete
subgraph with the largest possible number of vertices. We propose a new exact algorithm …
subgraph with the largest possible number of vertices. We propose a new exact algorithm …
Detecting a most closeness-central clique in complex networks
Centrality is a powerful concept for detecting influential components of a network applicable
to various areas such as analysis of social, collaboration, and biological networks. In this …
to various areas such as analysis of social, collaboration, and biological networks. In this …
Learning from survey propagation: a neural network for MAX-E-3-SAT
R Marino - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Many natural optimization problems are NP-hard, which implies that they are probably hard
to solve exactly in the worst-case. However, it suffices to get reasonably good solutions for …
to solve exactly in the worst-case. However, it suffices to get reasonably good solutions for …
A matheuristic approach for the b-coloring problem using integer programming and a multi-start multi-greedy randomized metaheuristic
Given a graph G=(V, E), the b-coloring problem consists in attributing a color to every vertex
in V such that adjacent vertices receive different colors, every color has a b-vertex, and the …
in V such that adjacent vertices receive different colors, every color has a b-vertex, and the …
A unified framework for multistage mixed integer linear optimization
We introduce a unified framework for the study of multilevel mixed integer linear optimization
problems and multistage stochastic mixed integer linear optimization problems with …
problems and multistage stochastic mixed integer linear optimization problems with …
Obtaining the Grundy chromatic number: How bad can my greedy heuristic coloring be?
Given a simple undirected graph G, its Grundy chromatic number Γ (G)(or Grundy number)
defines the worst-case behavior for the well-known and widely-used greedy first-fit coloring …
defines the worst-case behavior for the well-known and widely-used greedy first-fit coloring …