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cs.AI2025
REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models
Diego Forniés-Tabuenca, Alejandro Uribe, Urtzi Otamendi +3
Multi-objective optimization is fundamental in complex decision-making tasks. Traditional algorithms, while effective, often demand extensive problem-specific modeling and struggle…
cs.AI2024
Exploring Multi-Agent Reinforcement Learning for Unrelated Parallel Machine Scheduling
Maria Zampella, Urtzi Otamendi, Xabier Belaunzaran +4
Scheduling problems pose significant challenges in resource, industry, and operational management. This paper addresses the Unrelated Parallel Machine Scheduling Problem (UPMS) wit…