HiGAT-AC: Hierarchical Graph Attention with Actor-Critic for Scalable Multi-Objective Workflow Scheduling

As scientific workflows grow more complex and green computing becomes a priority, efficient multi-objective scheduling is essential to optimize makespan, cost, and energy consumption for large task graphs. However, existing methods often suffer from scalability bottlenecks and insufficient modeling...

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Autori principali:	Can Wu, Haili Xiao, Xiaoning Wang, Yining Zhao, Shasha Lu, Rong He
Natura:	Artigo
Lingua:	Inglês
Pubblicazione:	MDPI AG 2026-06-01
Serie:	Applied Sciences
Soggetti:	workflow scheduling graph attention networks reinforcement learning multi-objective optimization
Accesso online:	https://www.mdpi.com/2076-3417/16/12/5777
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