Deep Reinforcement Learning Approach for Maintenance Planning in a Flow-Shop Scheduling Problem
Contributo in Atti di convegno
Data di Pubblicazione:
2022
Citazione:
Deep Reinforcement Learning Approach for Maintenance Planning in a Flow-Shop Scheduling Problem / Marchesano, M.G., Staiano, L., Guizzi, G., Castellano, D., Popolo, V.. - 355:(2022), pp. 385-399. (21st International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2022 Kitakyushu 20-22 September 2022) [10.3233/FAIA220268].
Tipologia CRIS:
Relazione in Atti di Convegno
Keywords:
Decentralised Manufacturing Planning and Control system; Deep Reinforcement Learning; Flow-shop; Industry 4.0; Maintenance;
Elenco autori:
Marchesano, M. G.; Staiano, L.; Guizzi, G.; Castellano, D.; Popolo, V.
Link alla scheda completa:
Titolo del libro:
Frontiers in Artificial Intelligence and Applications
Pubblicato in: