activity
20042026
most citedAn optimization model for line planning and timetabling in automated urban metro subway networks

55 citations · 229 across the 44 of their papers we have counts for

collaborators

48 papers

math.OC2026

Optimization of Kinetic--Stoichiometric Growth Bounds over Autocatalytic Subnetworks

Víctor Blanco, Gabriel González

Autocatalytic subnetworks govern sustained production and balanced growth in chemical reaction systems and can be naturally represented as directed multihypergraphs that jointly en…

math.OC2025

Exact Matrix Seriation through Mathematical Optimization: Stress and Effectiveness-Based Models

Víctor Blanco, Alfredo Marín, Justo Puerto

Matrix seriation, the problem of permuting the rows and columns of a matrix to uncover latent structure, is a fundamental technique in data science, particularly in the visualizati…

math.OC2025

Linear, nested, and quadratic ordered measures: Computation and incorporation into optimization problems

Victor Blanco, Miguel A. Pozo, Justo Puerto +1

In this paper we address a unified mathematical optimization framework to compute a wide range of measures used in most operations research and data science contexts. The goal is t…

math.OC2024

Fixed Topology Minimum-Length Trees with Neighborhoods

Víctor Blanco, Gabriel González, Justo Puerto

In this paper, we introduce the Fixed Topology Minimum-Length Tree with Neighborhood Problem, which aims to embed a rooted tree-shaped graph into a -dimensional metric space whi…

math.OC2022★ 2 cited

Intra-facility equity in discrete and continuous -facility location problems

Víctor Blanco, Alfredo Marín, Justo Puerto

We consider facility location problems with a new form of equity criterion. Demand points have preference order on the sites where the plants can be located. The goal is to find th…

math.OC2022

A Mathematical Programming Approach to Optimal Classification Forests

Víctor Blanco, Alberto Japón, Justo Puerto +1

This paper introduces Weighted Optimal Classification Forests (WOCFs), a new family of classifiers that takes advantage of an optimal ensemble of decision trees to derive accurate…