Dirk Thierens
About
In The Last Decade
Dirk Thierens
77 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 1.8k
- Computational Theory and Mathematics 1.3k
- Management Science and Operations Research 236
- Industrial and Manufacturing Engineering 229
- Control and Systems Engineering 175
Countries citing papers authored by Dirk Thierens
This map shows the geographic impact of Dirk Thierens'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 Dirk Thierens with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dirk Thierens more than expected).
Fields of papers citing papers by Dirk Thierens
This network shows the impact of papers produced by Dirk Thierens. 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 Dirk Thierens. The network helps show where Dirk Thierens may publish in the future.
Co-authorship network of co-authors of Dirk Thierens
This figure shows the co-authorship network connecting the top 25 collaborators of Dirk Thierens. A scholar is included among the top collaborators of Dirk Thierens 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 Dirk Thierens. Dirk Thierens is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 33 | |
| 3 | 2 | |
| 4 | Adapted Maximum-Likelihood Gaussian Models for Numerical Optimization with Continuous EDAs | 5 |
| 5 | An Adaptive Pursuit Strategy for Allocating Operator Probabilities. | 1 |
| 6 | Predictive measures for problem representation and genetic operator design | 1 |
| 7 | On the design and analysis of competent GAs | 1 |
| 8 | Crossing the road to efficient IDEAs for permutation problems | 17 |
| 9 | Multi-objective mixture-based iterated density estimation evolutionary algorithms | 36 |
| 10 | Linkage information processing in distribution estimation algorithms | 46 |
| 11 | On the modelling of evolutionary algorithms | 2 |
| 12 | An algorithmic framework for density estimation based evolutionary algorithms | 25 |
| 13 | Estimating the significant non-linearities in the genome problem-coding | 7 |
| 14 | On the scalability of simple genetic algorithms | 1 |
| 15 | Robust genetic algorithms for high quality map labeling | 3 |
| 16 | Transmission function models of infinite population genetic algorithms | 2 |
| 17 | Selection schemes, elitist recombination, and selection intensity | 38 |
| 18 | Special Issue on Genetic Algorithms. Toward a Better Understanding of Mixing in Genetic Algorithms. | 2 |
| 19 | 55 | |
| 20 | Mixing in Genetic Algorithms | 115 |
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.