A novel learning model with dynamic heterogeneous graph network for uncertain multimode resource-constrained project scheduling problem

This paper addresses a multi-scenario multi-mode resource-constrained project scheduling problem with the goal of minimizing both the makespan and cost of the project. In order to visualize the changing process of modes and priority relationships in a project, a dynamic activity-mode network graph i...

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Vydáno v:	Computers & operations research Ročník 186; s. 107319
Hlavní autoři:	Wang, Zheng, Liu, Huiran, Fan, Xiaojun
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.02.2026
Témata:	Dynamic heterogeneous graph neural network Multimode resource-constrained scheduling Reinforcement learning algorithm Scenario-based uncertainty Trade-off time and cost Dynamic heterogeneous graph neural network Multimode resource-constrained scheduling Trade-off time and cost Scenario-based uncertainty Reinforcement learning algorithm
ISSN:	0305-0548
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