A modified multi-agent proximal policy optimization algorithm for multi-objective dynamic partial-re-entrant hybrid flow shop scheduling problem

This paper extends a novel model for modern flexible manufacturing systems: the multi-objective dynamic partial-re-entrant hybrid flow shop scheduling problem (MDPR-HFSP). The model considers partial-re-entrant processing, dynamic disturbance events, green manufacturing demand, and machine workload....

Celý popis

Podrobná bibliografia

Vydané v:	Engineering applications of artificial intelligence Ročník 140; s. 109688
Hlavní autori:	Wu, Jiawei, Liu, Yong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 15.01.2025
Predmet:	Deep reinforcement learning Dynamic scheduling Multi-agent Multi-objective optimization Partial-re-entrant hybrid flow shop Proximal policy optimization Multi-agent Dynamic scheduling Deep reinforcement learning Proximal policy optimization Multi-objective optimization Partial-re-entrant hybrid flow shop
ISSN:	0952-1976
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!