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.
Optimization of global production scheduling with deep reinforcement learning
2018264 citationsAndré Reichstaller, Alexander Knapp et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Alexander Knapp
Since
Specialization
Citations
This map shows the geographic impact of Alexander Knapp'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 Alexander Knapp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Knapp more than expected).
This network shows the impact of papers produced by Alexander Knapp. 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 Alexander Knapp. The network helps show where Alexander Knapp may publish in the future.
Co-authorship network of co-authors of Alexander Knapp
This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Knapp.
A scholar is included among the top collaborators of Alexander Knapp 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 Alexander Knapp. Alexander Knapp is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Seebach, Hella, et al.. (2019). Adaptive tests for adaptive systems: the need for new concepts in testing for future software systems. OPUS (Augsburg University).
Knapp, Alexander, Markus Roggenbach, & Bernd–Holger Schlingloff. (2015). Automating Test Case Selection in Model-Based Software Product Line Development. 9(2). 153–175.
Koch, Nora, Alexander Knapp, Gefei Zhang, & Hubert Baumeister. (2007). UML-Based Web Engineering:An Approach Based on Standards. Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU).36 indexed citations
Vallecillo, Antonio, Nora Koch, Cristina Cachero, et al.. (2007). MDWEnet: A Practical Approach to Achieving Interoperability of Model-Driven Web Engineering Methods. RUA, Repositorio Institucional de la Universidad de Alicante (Universidad de Alicante). 261. 1–10.16 indexed citations
Knapp, Alexander & Gefei Zhang. (2006). Model transformations for integrating and validating web application models. OPUS (Augsburg University). 115–128.9 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.