# Optimization of global production scheduling with deep reinforcement learning

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/optimization-of-global-production-scheduling-with-deep-reinforcement-learning/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Bernd Waschneck,André Reichstaller,Lenz Belzner,Thomas Altenmüller,Thomas Bauernhansl,Alexander Knapp,Andreas Kyek |
| Citations | 359 |
| DOI | 10.1016/j.procir.2018.03.212 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | diamond |
| OA URL | https://www.sciencedirect.com/science/article/pii/S221282711830372X/pdf |
| OpenAlex ID | https://openalex.org/W2811338889 |
| Type | article |
| Year | 2018 |

## Paper authors

- [Thomas Bauernhansl](https://scholariq.org/researchers/thomas-bauernhansl/)

## Paper journal

- [Procedia CIRP](https://scholariq.org/journals/procedia-cirp/)

## Paper primary topic

- [Scheduling and Optimization Algorithms](https://scholariq.org/topics/scheduling-and-optimization-algorithms/)

## Paper topics

- [Scheduling and Optimization Algorithms](https://scholariq.org/topics/scheduling-and-optimization-algorithms/)
- [Advanced Manufacturing and Logistics Optimization](https://scholariq.org/topics/advanced-manufacturing-and-logistics-optimization/)
- [Reinforcement Learning in Robotics](https://scholariq.org/topics/reinforcement-learning-in-robotics/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.