Sebastian Lang

1.0k total citations · 1 hit paper
50 papers, 617 citations indexed

About

Sebastian Lang is a scholar working on Industrial and Manufacturing Engineering, Management Information Systems and Computer Networks and Communications. According to data from OpenAlex, Sebastian Lang has authored 50 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Industrial and Manufacturing Engineering, 10 papers in Management Information Systems and 8 papers in Computer Networks and Communications. Recurrent topics in Sebastian Lang's work include Scheduling and Optimization Algorithms (15 papers), Assembly Line Balancing Optimization (11 papers) and Flexible and Reconfigurable Manufacturing Systems (10 papers). Sebastian Lang is often cited by papers focused on Scheduling and Optimization Algorithms (15 papers), Assembly Line Balancing Optimization (11 papers) and Flexible and Reconfigurable Manufacturing Systems (10 papers). Sebastian Lang collaborates with scholars based in Germany, United States and China. Sebastian Lang's co-authors include Tobias Reggelin, Marcel Müller, Ilya Jackson, Dmitry Ivanov, A. von Mayrhauser, Michael Schenk, Florian Müller, Bingyuan Hong, Juri Tolujew and Gernot A. Fink and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Transactions on Software Engineering.

In The Last Decade

Sebastian Lang

45 papers receiving 582 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A review on reinforcement learning algorithms and applications in supply chain management

2022 162 citations Ilya Jackson, Marcel Müller et al. International Journal of Production Research profile →

Peers

Sebastian Lang

IME

MIS

SM

AI

IS

Fengtian Chang China

Jiapeng Yu China

Alan de Pennington United Kingdom

Jochen Deuse Germany

Weinan Sha China

Ehsan Teymourian Iran

Abe Zeid United States

Gaurav Singh Australia

Cheng Qian China

Edward Elson Kosasih United Kingdom

Fengtian Chang China

Sebastian Lang

441 ×1.4

IME

56 ×0.5

MIS

75 ×1.0

SM

87 ×1.2

AI

57 ×0.8

IS

Citations per year, relative to Sebastian Lang Sebastian Lang (= 1×) peers Fengtian Chang

Countries citing papers authored by Sebastian Lang

Since Specialization

Citations

This map shows the geographic impact of Sebastian Lang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sebastian Lang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sebastian Lang more than expected).

Fields of papers citing papers by Sebastian Lang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sebastian Lang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sebastian Lang. The network helps show where Sebastian Lang may publish in the future.

Co-authorship network of co-authors of Sebastian Lang

This figure shows the co-authorship network connecting the top 25 collaborators of Sebastian Lang. A scholar is included among the top collaborators of Sebastian Lang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sebastian Lang. Sebastian Lang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

1.

Reggelin, Tobias, et al.. (2025). Advancing robotic systems with Ensemble and Modular Deep Learning: research idea and framework. Procedia Computer Science. 253. 2557–2566.

2.

Wang, Xiaofeng, Duk Kyung Kim, Ziyuan Yang, et al.. (2025). Research on Infrared Small Target Detection Algorithm Based on Foreground Moving Target and Deep Learning for Space Detection. Space Science & Technology. 5.

3.

Reggelin, Tobias, et al.. (2024). Using Sentiment Analysis to Detect Disruptive Events in Supply Chains. IFAC-PapersOnLine. 58(19). 864–869. 2 indexed citations

4.

Reggelin, Tobias, et al.. (2024). An LSTM network-based genetic algorithm for integrated procurement and scheduling optimisation. International Journal of Production Research. 63(11). 4036–4065. 1 indexed citations

5.

Lang, Sebastian, et al.. (2024). A transformer-based deep reinforcement learning approach for dynamic parallel machine scheduling problem with family setups. Journal of Intelligent Manufacturing. 36(7). 4735–4768. 5 indexed citations

6.

Lang, Sebastian, et al.. (2024). Optimizing Safety Stock Placement in Large Real-World Automotive Supply Networks Using the Guaranteed-Service Model. Proceedings of the ... Annual Hawaii International Conference on System Sciences.

7.

Lang, Sebastian, et al.. (2023). A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups. Journal of Intelligent Manufacturing. 35(3). 1107–1140. 21 indexed citations

8.

Mebarki, Nasser, Sebastian Lang, Tobias Reggelin, et al.. (2022). Using Knowledge Graphs and Human-Centric Artificial Intelligence for Reconfigurable Supply Chains: A Research Framework. IFAC-PapersOnLine. 55(10). 1693–1698. 6 indexed citations

9.

Lang, Sebastian, et al.. (2022). Integration of the A2C Algorithm for Production Scheduling in a Two-Stage Hybrid Flow Shop Environment. Procedia Computer Science. 200. 585–594. 10 indexed citations

10.

Lang, Sebastian, et al.. (2022). A brief introduction to deploy Amazon Web Services for online discrete-event simulation. Procedia Computer Science. 200. 386–393. 7 indexed citations

11.

Lang, Sebastian, et al.. (2021). Modeling Production Scheduling Problems as Reinforcement Learning Environments based on Discrete-Event Simulation and OpenAI Gym. IFAC-PapersOnLine. 54(1). 793–798. 11 indexed citations

12.

Reggelin, Tobias, et al.. (2020). Mesoscopic discrete-rate-based simulation models for production and logistics planning. Journal of Simulation. 16(5). 448–457. 5 indexed citations

13.

Reggelin, Tobias, et al.. (2020). Assigning dispatching rules using a genetic algorithm to solve a hybrid flow shop scheduling problem. Procedia Manufacturing. 42. 442–449. 25 indexed citations

14.

Lang, Sebastian, et al.. (2020). Integration of Deep Reinforcement Learning and Discrete-Event Simulation for Real-Time Scheduling of a Flexible Job Shop Production. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 3057–3068. 47 indexed citations

15.

Jackson, Ilya, et al.. (2019). Metamodelling of Inventory-Control Simulations Based on a Multilayer Perceptron. Transport and Telecommunication Journal. 20(3). 251–259. 7 indexed citations

16.

Lang, Sebastian, et al.. (2019). Mixed reality in production and logistics: Discussing the application potentials of Microsoft HoloLensTM. Procedia Computer Science. 149. 118–129. 25 indexed citations

17.

Lang, Sebastian, et al.. (2018). Scheduling Approach for the Simulation of a Sustainable Resource Supply Chain. SHILAP Revista de lepidopterología. 2(3). 12–12. 1 indexed citations

18.

Lang, Sebastian, et al.. (2016). Emulation as part of an integrated logistics learning environment. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 134–140. 1 indexed citations

19.

Lang, Sebastian & A. von Mayrhauser. (2002). Building a research infrastructure for program comprehension observations. 10. 165–169. 1 indexed citations

20.

Mayrhauser, A. von & Sebastian Lang. (1999). A coding scheme to support systematic analysis of software comprehension. IEEE Transactions on Software Engineering. 25(4). 526–540. 30 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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