Transferencia | GRAFO Research Group

Optimization in Asset Selection for Asset-Backed Structured Finance Operations

Tue, 20 Jan 2026 00:00:00 +0000

Principal investigators: J. Manuel Colmenar, Eduardo García Pardo
Department: Computer Science and Statistics
Funding entity: Confidential (not disclosed)
Period: January 2026 – July 2026

Description

This R&D contract project addresses the optimization of asset selection in the context of asset-backed structured finance operations. Optimization models and algorithms are developed to efficiently select asset portfolios while satisfying the financial and risk criteria specific to this type of operation.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Development of Advanced AI and Automation Techniques in Forecasting, Staffing and Scheduling for Workforce Management

Fri, 09 May 2025 00:00:00 +0000

Principal investigators: Jesús Sánchez-Oro
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: May 2025 – February 2026

Description

This R&D contract project focuses on the development of advanced artificial intelligence and automation techniques applied to demand forecasting, staffing planning, and shift scheduling in the context of workforce management. The goal is to improve the efficiency and quality of generated plans by integrating predictive models with optimization algorithms.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Optimizing Short- and Long-Term Truck Routing and Barge Routing in Oil Logistics

Wed, 01 Jan 2025 00:00:00 +0000

Principal investigators: Sergio Cavero, Javier Yuste
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: January 2025 – September 2026

Description

This R&D contract project addresses the optimization of distribution operations in oil logistics, both in the short and long term. The work focuses on designing algorithms and optimization models for routing planning of tanker trucks and barges, taking into account operational, labor, and capacity constraints specific to the industry.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Advisory Services in Industrial Project Optimization

Mon, 30 Sep 2024 00:00:00 +0000

Principal investigators: Jesús Sánchez-Oro
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: September 2024 – July 2025

Description

This R&D contract project consists of providing specialized advisory services in optimization techniques applied to industrial projects. The work encompasses the analysis of real-world optimization problems, the design of mathematical models, and the proposal of algorithms tailored to the client’s specific needs.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Comprehensive Operations Optimization

Fri, 27 Sep 2024 00:00:00 +0000

Principal investigators: José Manuel Colmenar Verdugo, Raúl Martín Santamaría
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: September 2024 – March 2025

Description

This R&D contract project addresses the comprehensive optimization of operations in an industrial or business environment. Models and algorithms are designed to improve the overall efficiency of operational processes, considering multiple objectives and constraints simultaneously.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Optimization of Production through Lot-Sizing and Scheduling on Parallel Production Lines

Thu, 01 Feb 2024 00:00:00 +0000

Principal investigators: Sergio Cavero, Eduardo G. Pardo
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: February 2024 – December 2024

Description

This R&D contract project addresses the optimization of industrial production processes, specifically the joint problem of lot-sizing and scheduling on parallel production lines. Models and algorithms are designed to minimize production costs and times while satisfying capacity constraints and delivery deadlines.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Optimizer for Shift Schedules and Timetables in Companies and Educational Institutions using Matheuristic Techniques (Smartiming)

Mon, 01 Jan 2024 00:00:00 +0000

Principal investigators: Jesús Sánchez-Oro, Sergio Pérez Peló
Department: Computer Science and Statistics
Funding entity: Confidential (not disclosed)

Description

Smartiming is an R&D contract project focused on developing an optimizer for shift schedules and timetables for companies and educational institutions. By using matheuristic techniques — combining mathematical programming methods with metaheuristics — the system generates high-quality schedules that respect the operational, educational, and organizational constraints of each entity.

The resulting tool allows the shift assignment, duty planning, and class timetabling processes to be automated and significantly improved, reducing management costs and increasing end-user satisfaction.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

AI-Driven Optimization of Chess Preparation for High-Performance Players

Wed, 20 Dec 2023 00:00:00 +0000

Principal investigators: Isaac Lozano Osorio, Jesús Sánchez-Oro
Funding entity: Spanish Chess Federation (Federación Española de Ajedrez)
Internal reference: M3341
Period: December 2023 – December 2024

Description

This technology transfer project, funded by the Spanish Chess Federation, aimed to apply Artificial Intelligence techniques to optimize the competitive preparation of high-performance chess players.

A remotely configurable analysis server was designed and deployed, with the analysis module tuned specifically for high-performance use and installed on players’ workstations. Custom algorithms were developed to generate personalized reports for elite players, identifying playing patterns and preparing tailored strategies against specific opponents.

In addition, a web platform was built for high-performance players to centralise access to reports and preparation tools.

Impact

The results were most visibly demonstrated at the 2024 Chess Olympiad, where the Spanish team achieved its best historical results. The methodology was covered in national media:

Dissemination

The work was presented at leading conferences:

OSINT in Chess: The Secret Behind Spain’s Olympic Medals — RootedCON 2026, Track Rooted, Room 17
OSINT in Chess: The Secret Behind Spain’s Olympic Medals — HackRON 2026, Auditorio de Tenerife Adán Martín
We all work with patterns: how AI finds them in chess and in the classroom — IV International Congress on Chess and AI, Maó (Menorca), 25 April 2026

Development of Metaheuristic Algorithms for Optimization Problems

Tue, 01 Sep 2020 00:00:00 +0000

Principal investigators: Abraham Duarte Muñoz, Jesús Sánchez-Oro
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: September 2020 – February 2021

Description

This R&D contract project focuses on the design and development of metaheuristic algorithms for solving complex optimization problems. The work encompasses the analysis of real-world problems, the proposal of advanced algorithmic techniques, and the experimental validation of the solutions obtained.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.

Improvements and Corrections to an Optimization Algorithm for Solar Panel Placement

Tue, 10 Dec 2019 00:00:00 +0000

Principal investigators: Abraham Duarte Muñoz, Jesús Sánchez-Oro
Type: R&D Contract Project
Funding entity: Confidential (not disclosed)
Period: December 2019 – March 2020

Description

This R&D contract project involved improving and correcting an existing optimization algorithm for the optimal placement of solar panel installations. The work included analysing the prior algorithm, identifying and fixing errors, and incorporating improvements to its performance and accuracy.

For confidentiality reasons, no further information is provided about the contracting entity or the specific details of the project.