# Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/deep-reinforcement-learning-for-machine-scheduling-methodology-the-state-of-the-3/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Maziyar Khadivi,Todd Charter,Marjan Yaghoubi,Masoud Jalayer,Maryam Ahang,Ardeshir Shojaeinasab,Homayoun Najjaran |
| Citations | 41 |
| DOI | 10.1016/j.cie.2025.110856 |
| Fields | Computer Science,Engineering |
| Open Access | false |
| OA Status | closed |
| OpenAlex ID | https://openalex.org/W4406141308 |
| Type | article |
| Year | 2025 |

## Paper authors

- [Marjan Yaghoubi](https://scholariq.org/researchers/marjan-yaghoubi/)
- [Todd Charter](https://scholariq.org/researchers/todd-charter/)
- [Masoud Jalayer](https://scholariq.org/researchers/masoud-jalayer/)
- [Ardeshir Shojaeinasab](https://scholariq.org/researchers/ardeshir-shojaeinasab/)
- [Homayoun Najjaran](https://scholariq.org/researchers/homayoun-najjaran/)

## Paper journal

- [Computers & Industrial Engineering](https://scholariq.org/journals/computers-and-industrial-engineering/)

## 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/)
- [Reinforcement Learning in Robotics](https://scholariq.org/topics/reinforcement-learning-in-robotics/)
- [Optimization and Search Problems](https://scholariq.org/topics/optimization-and-search-problems/)

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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.