Knowledge-enhanced multi-objective memetic algorithm for energy-efficient flexible job shop scheduling with limited multi-load automated guided vehicles

In alignment with the national call for energy conservation and emission reduction, energy-efficient scheduling in manufacturing, especially intelligent workshops, has become a key research area. Automated guided vehicles (AGVs), as the core component of intelligent logistics systems, especially in...

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Vydané v:	Engineering applications of artificial intelligence Ročník 159; s. 111771
Hlavní autori:	Fan, Lianghua, Lei, Qi, Song, Yuchuan, Liu, Yang, Yang, Yunfan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Ltd 08.11.2025
Predmet:	Energy-efficient flexible job shop scheduling Memetic algorithm Multi-load automated guided vehicles Multi-objective optimization Total energy consumption Multi-load automated guided vehicles Memetic algorithm Multi-objective optimization Total energy consumption Energy-efficient flexible job shop scheduling
ISSN:	0952-1976
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