A new strategic marketing management model for the specificities of E-commerce in the supply chain
The study seeks to answer the question of what strategic directions and opportunities we
have for business in the midst of the info-communication changes of our time. In this …
have for business in the midst of the info-communication changes of our time. In this …
Neural algorithmic reasoning for combinatorial optimisation
Solving NP-hard/complete combinatorial problems with neural networks is a challenging
research area that aims to surpass classical approximate algorithms. The long-term …
research area that aims to surpass classical approximate algorithms. The long-term …
A pairwise fair and community-preserving approach to k-center clustering
Clustering is a foundational problem in machine learning with numerous applications. As
machine learning increases in ubiquity as a backend for automated systems, concerns …
machine learning increases in ubiquity as a backend for automated systems, concerns …
Approximation algorithms for the vertex k-center problem: Survey and experimental evaluation
The vertex k-center problem is a classical NP-Hard optimization problem with application to
Facility Location and Clustering among others. This problem consists in finding a subset of …
Facility Location and Clustering among others. This problem consists in finding a subset of …
p-Center Problems
A p-center is a minimax solution that consists of a set of p points minimizing the maximum
distance between a demand point and a closest point belonging to that set. We present …
distance between a demand point and a closest point belonging to that set. We present …
Burning graphs through farthest-first traversal
Graph burning is a process to determine the spreading of information in a graph. If a
sequence of vertices burns all the vertices of a graph by following the graph burning …
sequence of vertices burns all the vertices of a graph by following the graph burning …
Scalable and Globally Optimal Generalized L₁ K-center Clustering via Constraint Generation in Mixed Integer Linear Programming
The k-center clustering algorithm, introduced over 35 years ago, is known to be robust to
class imbalance prevalent in many clustering problems and has various applications such …
class imbalance prevalent in many clustering problems and has various applications such …
Solving the capacitated vertex k-center problem through the minimum capacitated dominating set problem
The capacitated vertex k-center problem receives as input a complete weighted graph and a
set of capacity constraints. Its goal is to find a set of k centers and an assignment of vertices …
set of capacity constraints. Its goal is to find a set of k centers and an assignment of vertices …
Reasoning Algorithmically in Graph Neural Networks
D Numeroso - arxiv preprint arxiv:2402.13744, 2024 - arxiv.org
The development of artificial intelligence systems with advanced reasoning capabilities
represents a persistent and long-standing research question. Traditionally, the primary …
represents a persistent and long-standing research question. Traditionally, the primary …
Min-Max-Min Optimization with Smooth and Strongly Convex Objectives
We consider min-max-min optimization with smooth and strongly convex objectives. Our
motivation for studying this class of problems stems from its connection to the-center …
motivation for studying this class of problems stems from its connection to the-center …