14 citations · 38 across the 10 of their papers we have counts for
10 papers
Profiling Lightweight Large Language Models
Tomohiro Harada, Enrique Alba, Gabriel Luque
Lightweight large language models (LLMs) are increasingly being deployed locally on personal computers and are expected to play a growing role in resource-constrained edge and mobi…
Robust Multi-Objective Optimization for Bicycle Rebalancing in Shared Mobility Systems
Diego Daniel Pedroza-Perez, Gabriel Luque, Sergio Nesmachnow +1
Dock-based bike-sharing systems exhibit spatial imbalances between bicycle supply and user demand, often addressed through overnight truck-based rebalancing. This work studies stat…
A Methodology for Effective Surrogate Learning in Complex Optimization
Tomohiro Harada, Enrique Alba, Gabriel Luque
Solving complex problems requires continuous effort in developing theory and practice to cope with larger, more difficult scenarios. Working with surrogates is normal for creating…
Green Optimization: Energy-aware Design of Metaheuristics by Using Machine Learning Surrogates to Cope with Real Problems
Tomohiro Harada, Enrique Alba, Gabriel Luque
Addressing real-world optimization challenges requires not only advanced metaheuristics but also continuous refinement of their internal mechanisms. This paper explores the integra…
Energy-Aware Metaheuristics
Enrique Alba, Tomohiro Harada, Gabriel Luque
This paper presents a principled framework for designing energy-aware metaheuristics that operate under fixed energy budgets. We introduce a unified operator-level model that quant…
Energy and Quality of Surrogate-Assisted Search Algorithms: a First Analysis
Tomohiro Harada, Enrique Alba, Gabriel Luque
Solving complex real problems often demands advanced algorithms, and then continuous improvements in the internal operations of a search technique are needed. Hybrid algorithms, pa…
Combinatorial Optimization with Quantum Computers
Francisco Chicano, Gabiel Luque, Zakaria Abdelmoiz Dahi +1
Quantum computers leverage the principles of quantum mechanics to do computation with a potential advantage over classical computers. While a single classical computer transforms o…
Optimising Communication Overhead in Federated Learning Using NSGA-II
José Ángel Morell, Zakaria Abdelmoiz Dahi, Francisco Chicano +2
Federated learning is a training paradigm according to which a server-based model is cooperatively trained using local models running on edge devices and ensuring data privacy. The…
A Fresh Approach to Evaluate Performance in Distributed Parallel Genetic Algorithms
Tomohiro Harada, Enrique Alba, Gabriel Luque
This work proposes a novel approach to evaluate and analyze the behavior of multi-population parallel genetic algorithms (PGAs) when running on a cluster of multi-core processors.…
Elementary Components of the Quadratic Assignment Problem
Francisco Chicano, Gabriel Luque, Enrique Alba
The Quadratic Assignment Problem (QAP) is a well-known NP-hard combinatorial optimization problem that is at the core of many real-world optimization problems. We prove that QAP ca…