An end-to-end deep reinforcement learning method based on graph neural network for distributed job-shop scheduling problem

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 121756 - 121756

Опубликована: Сен. 27, 2023

Язык: Английский

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Smart scheduling of dynamic job shop based on discrete event simulation and deep reinforcement learning

Journal of Intelligent Manufacturing, Год журнала: 2023, Номер 35(6), С. 2593 - 2610

Опубликована: Июнь 24, 2023

Язык: Английский

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A Double Deep Q-Network framework for a flexible job shop scheduling problem with dynamic job arrivals and urgent job insertions

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 133, С. 108487 - 108487

Опубликована: Апрель 26, 2024

Язык: Английский

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An adaptive multi-objective multi-task scheduling method by hierarchical deep reinforcement learning

Applied Soft Computing, Год журнала: 2024, Номер 154, С. 111342 - 111342

Опубликована: Фев. 3, 2024

Язык: Английский

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Two-stage double deep Q-network algorithm considering external non-dominant set for multi-objective dynamic flexible job shop scheduling problems

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 90, С. 101660 - 101660

Опубликована: Июль 18, 2024

Язык: Английский

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Multi-agent deep reinforcement learning-based approach for dynamic flexible assembly job shop scheduling with uncertain processing and transport times

Expert Systems with Applications, Год журнала: 2025, Номер unknown, С. 126441 - 126441

Опубликована: Янв. 1, 2025

Язык: Английский

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3D Vision robot online packing platform for deep reinforcement learning

Robotics and Computer-Integrated Manufacturing, Год журнала: 2025, Номер 94, С. 102941 - 102941

Опубликована: Янв. 15, 2025

Язык: Английский

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Scheduling of Resource Allocation Systems with Timed Petri Nets: A Survey

ACM Computing Surveys, Год журнала: 2022, Номер 55(11), С. 1 - 27

Опубликована: Ноя. 3, 2022

Resource allocation systems (RASs) belong to a kind of discrete event system commonly seen in the industry. In such systems, available resources are allocated concurrently running processes optimize some performance criteria. Search strategies reachability graph (RG) timed Petri net (PN) attracted much attention past decades cope with RAS scheduling problems (RSPs), since PNs very suitable model and analyze RASs their RGs fully reflect systems’ behavior. However, there has been no existing related survey review paper till now. this work, we present tutorial comprehensive literature RG-based RSP methods. Many state-of-the-art reviewed summarized. First, framework RSPs classify terms resource usage structures. The differences relations among also given. Then, introduce PN construction methods for objectives search RSPs. Next, summarize different heuristic functions adopted frequently used A * solve Finally, discuss important future research directions open issues.

Язык: Английский

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A cooperative hierarchical deep reinforcement learning based multi-agent method for distributed job shop scheduling problem with random job arrivals

Computers & Industrial Engineering, Год журнала: 2023, Номер 185, С. 109650 - 109650

Опубликована: Окт. 4, 2023

Язык: Английский

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Deep reinforcement learning for dynamic distributed job shop scheduling problem with transfers

Expert Systems with Applications, Год журнала: 2024, Номер 251, С. 123970 - 123970

Опубликована: Апрель 17, 2024

Язык: Английский

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