Multi-Agent Reinforcement Learning for Extended Flexible Job Shop Scheduling

An extended flexible job scheduling problem is presented with characteristics of technology and path flexibility (dual flexibility), varied transportation time, and an uncertain environment. The scheduling can greatly increase efficiency and security in complex scenarios, e.g., distributed vehicle m...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Machines (Basel) Ročník 12; číslo 1; s. 8
Hlavní autori:	Peng, Shaoming, Xiong, Gang, Yang, Jing, Shen, Zhen, Tamir, Tariku Sinshaw, Tao, Zhikun, Han, Yunjun, Wang, Fei-Yue
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.01.2024
Predmet:	Adaptability Aircraft industry Aircraft maintenance Algorithms Data mining Decision making Energy consumption Fixed base operators industry Flexibility flexible job shop Heuristic Job shop scheduling Job shops Machine learning Markov processes Mathematical optimization Mathematical programming multi-agent reinforcement learning Multiagent systems Optimization Optimization algorithms path flexibility Process planning production planning and scheduling Robots Scheduling technological flexibility Transportation equipment industry China
ISSN:	2075-1702, 2075-1702
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!