Solving large flexible job shop scheduling instances by generating a diverse set of scheduling policies with deep reinforcement learning. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (CoRR, 2023)

Single Agent Formulation for Reinforcement Learning Based Routing of Urban Last Mile Logistics with Platooning Vehicles. - Nagore Bravo; Imanol Echeverria; Alain Andres; Ibai Lana (ITSC, 2024)

Multi-Assignment Scheduler: A New Behavioral Cloning Method for the Job-Shop Scheduling Problem. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (LION, 2024)

Offline reinforcement learning for job-shop scheduling problems. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (CoRR, 2024)

Diverse policy generation for the flexible job-shop scheduling problem via deep reinforcement learning with a novel graph representation. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (Eng. Appl. Artif. Intell., 2025)

Leveraging constraint programming in a deep learning approach for dynamically solving the flexible job-shop scheduling problem. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (Expert Syst. Appl., 2025)

Self-Evaluation for Job-Shop Scheduling. - Imanol Echeverria; Maialen Murua; Roberto Santana 001 (CoRR, 2025)