This map shows the geographic impact of Rob Zuidwijk'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 Rob Zuidwijk with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rob Zuidwijk more than expected).
This network shows the impact of papers produced by Rob Zuidwijk. 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 Rob Zuidwijk. The network helps show where Rob Zuidwijk may publish in the future.
Co-authorship network of co-authors of Rob Zuidwijk
This figure shows the co-authorship network connecting the top 25 collaborators of Rob Zuidwijk.
A scholar is included among the top collaborators of Rob Zuidwijk 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 Rob Zuidwijk. Rob Zuidwijk is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Zuidwijk, Rob. (2015). The value of big data to big ports. RePub (Erasmus University, Rotterdam). 2015(2). 14–16.2 indexed citations
8.
Zuidwijk, Rob, et al.. (2013). Joint Design and Pricing of Intermodal Port - Hinterland Network Services: Considering Economies of Scale and Service Time Constraints. RePub (Erasmus University, Rotterdam).7 indexed citations
9.
Zuidwijk, Rob & Albert Veenstra. (2010). The Value of Information in Container Transport: Leveraging the Triple Bottom Line. Data Archiving and Networked Services (DANS).3 indexed citations
10.
Srour, F. Jordan, et al.. (2010). MIPLIB Truckload PDPTW Instances Derived from a Real-World Drayage Case. Research Repository (Delft University of Technology).5 indexed citations
11.
Ketter, Wolfgang, Eric van Heck, & Rob Zuidwijk. (2010). Intelligent Personalized Trading Agents that facilitate Real-time Decisionmaking for Auctioneers and Buyers in the Dutch Flower Auctions. RePub (Erasmus University, Rotterdam).4 indexed citations
12.
Ketter, Wolfgang, et al.. (2009). An agent-based approach to improving resource allocation in the Dutch youth health care sector. Data Archiving and Networked Services (DANS). 2468–2479.3 indexed citations
Srour, F. Jordan, et al.. (2008). Multi Agent Systems in Logistics: A Literature and State-of-the-art Review. Data Archiving and Networked Services (DANS).11 indexed citations
15.
Zuidwijk, Rob. (2005). Linear Parametric Sensitivity Analysis of the Constraint Coefficient Matrix in Linear Programs. RePub (Erasmus University, Rotterdam).1 indexed citations
16.
Krikke, Harold, J.A.E.E. van Nunen, Rob Zuidwijk, & Roelof Kuik. (2004). E-business and circular supply chains, IT based integration of reverse logistics and installed base management. Lecture notes in economics and mathematical systems.1 indexed citations
17.
Zuidwijk, Rob, et al.. (2001). Numerical methods for decomposition of 2D signals by rotation and wavelet techniques. 1–20.
18.
Zuidwijk, Rob & Leo Kroon. (2000). INTEGER CONSTRAINTS FOR TRAIN SERIES CONNECTIONS. Data Archiving and Networked Services (DANS).2 indexed citations
19.
Zuidwijk, Rob & Paul M. de Zeeuw. (1999). The fast wavelet X-ray transform. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–24.1 indexed citations
20.
Zuidwijk, Rob. (1997). The wavelet X-ray transform. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–21.4 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.