Beatrice Ombuki-Berman

1.3k total citations
55 papers, 772 citations indexed

About

Beatrice Ombuki-Berman is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Control and Systems Engineering. According to data from OpenAlex, Beatrice Ombuki-Berman has authored 55 papers receiving a total of 772 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Artificial Intelligence, 30 papers in Computational Theory and Mathematics and 12 papers in Control and Systems Engineering. Recurrent topics in Beatrice Ombuki-Berman's work include Metaheuristic Optimization Algorithms Research (38 papers), Evolutionary Algorithms and Applications (29 papers) and Advanced Multi-Objective Optimization Algorithms (28 papers). Beatrice Ombuki-Berman is often cited by papers focused on Metaheuristic Optimization Algorithms Research (38 papers), Evolutionary Algorithms and Applications (29 papers) and Advanced Multi-Objective Optimization Algorithms (28 papers). Beatrice Ombuki-Berman collaborates with scholars based in Canada, South Africa and Australia. Beatrice Ombuki-Berman's co-authors include Andries P. Engelbrecht, Kyle Robert Harrison, Mario Ventresca, Yifeng Li, Sheridan Houghten, Joseph Alexander Brown, Alain Tchagang, James Paterson, Naser Ezzati‐Jivan and Shahryar Rahnamayan and has published in prestigious journals such as European Journal of Operational Research, BMC Bioinformatics and Information Sciences.

In The Last Decade

Beatrice Ombuki-Berman

52 papers receiving 756 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Beatrice Ombuki-Berman Canada 14 398 257 153 116 78 55 772
Jianping Luo China 15 384 1.0× 321 1.2× 190 1.2× 63 0.5× 62 0.8× 42 774
Surafel Luleseged Tilahun South Africa 13 333 0.8× 145 0.6× 101 0.7× 98 0.8× 65 0.8× 37 633
Ya-Hui Jia China 12 303 0.8× 164 0.6× 232 1.5× 58 0.5× 99 1.3× 29 689
Myriam Delgado Brazil 19 503 1.3× 244 0.9× 154 1.0× 128 1.1× 49 0.6× 87 899
Weian Guo China 14 309 0.8× 213 0.8× 55 0.4× 148 1.3× 216 2.8× 50 724
T.H. Lee Singapore 15 295 0.7× 170 0.7× 108 0.7× 97 0.8× 63 0.8× 47 747
Miren Nekane Bilbao Spain 12 365 0.9× 105 0.4× 94 0.6× 106 0.9× 153 2.0× 35 774
Tea Tušar Slovenia 14 285 0.7× 306 1.2× 51 0.3× 92 0.8× 85 1.1× 48 623
Qingling Zhu China 12 598 1.5× 597 2.3× 94 0.6× 96 0.8× 55 0.7× 28 893
Mario Andrés Muñoz Australia 15 477 1.2× 265 1.0× 91 0.6× 87 0.8× 54 0.7× 55 857

Countries citing papers authored by Beatrice Ombuki-Berman

Since Specialization
Citations

This map shows the geographic impact of Beatrice Ombuki-Berman'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 Beatrice Ombuki-Berman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Beatrice Ombuki-Berman more than expected).

Fields of papers citing papers by Beatrice Ombuki-Berman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beatrice Ombuki-Berman. 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 Beatrice Ombuki-Berman. The network helps show where Beatrice Ombuki-Berman may publish in the future.

Co-authorship network of co-authors of Beatrice Ombuki-Berman

This figure shows the co-authorship network connecting the top 25 collaborators of Beatrice Ombuki-Berman. A scholar is included among the top collaborators of Beatrice Ombuki-Berman 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 Beatrice Ombuki-Berman. Beatrice Ombuki-Berman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ombuki-Berman, Beatrice, et al.. (2024). A comparative study of evolutionary algorithms and particle swarm optimization approaches for constrained multi-objective optimization problems. Swarm and Evolutionary Computation. 91. 101742–101742. 6 indexed citations
2.
Li, Yifeng, et al.. (2024). Integrating transformers and many-objective optimization for drug design. BMC Bioinformatics. 25(1). 208–208. 3 indexed citations
3.
4.
Engelbrecht, Andries P., et al.. (2023). Cooperative coevolutionary multi-guide particle swarm optimization algorithm for large-scale multi-objective optimization problems. Swarm and Evolutionary Computation. 78. 101262–101262. 47 indexed citations
5.
Ombuki-Berman, Beatrice, et al.. (2022). Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems. Swarm Intelligence. 16(2). 143–168. 9 indexed citations
6.
Ombuki-Berman, Beatrice, et al.. (2021). Predicting Particle Swarm Optimization Control Parameters From Fitness Landscape Characteristics. 2289–2298. 3 indexed citations
7.
Engelbrecht, Andries P., et al.. (2021). An analysis of the impact of subsampling on the neural network error surface. Neurocomputing. 466. 252–264. 1 indexed citations
8.
Ombuki-Berman, Beatrice, et al.. (2020). NichePSO and the Merging Subswarm Problem. 17–22. 1 indexed citations
9.
Ombuki-Berman, Beatrice, et al.. (2019). Random Regrouping and Factorization in Cooperative Particle Swarm Optimization Based Large-Scale Neural Network Training. Neural Processing Letters. 51(1). 759–796. 1 indexed citations
10.
Harrison, Kyle Robert, Beatrice Ombuki-Berman, & Andries P. Engelbrecht. (2017). Optimal parameter regions for particle swarm optimization algorithms. 349–356. 17 indexed citations
11.
Harrison, Kyle Robert, Andries P. Engelbrecht, & Beatrice Ombuki-Berman. (2017). An adaptive particle swarm optimization algorithm based on optimal parameter regions. 1–8. 21 indexed citations
12.
Harrison, Kyle Robert, Andries P. Engelbrecht, & Beatrice Ombuki-Berman. (2017). Self-adaptive particle swarm optimization: a review and analysis of convergence. Swarm Intelligence. 12(3). 187–226. 102 indexed citations
13.
Ventresca, Mario, Kyle Robert Harrison, & Beatrice Ombuki-Berman. (2017). The bi-objective critical node detection problem. European Journal of Operational Research. 265(3). 895–908. 26 indexed citations
14.
Ombuki-Berman, Beatrice, et al.. (2016). Pareto-based many-objective optimization using knee points. 3678–3686. 13 indexed citations
15.
Harrison, Kyle Robert, Andries P. Engelbrecht, & Beatrice Ombuki-Berman. (2016). The sad state of self-adaptive particle swarm optimizers. 2. 431–439. 17 indexed citations
16.
Ombuki-Berman, Beatrice, et al.. (2015). Vector-evaluated particle swarm optimization with local search. 3410. 187–195. 2 indexed citations
17.
Ventresca, Mario, et al.. (2012). Automatic generation of graph models for complex networks by genetic programming. 711–718. 8 indexed citations
18.
Ombuki-Berman, Beatrice, et al.. (2010). An efficient genetic algorithm for the uncapacitated single allocation hub location problem. 190. 1–8. 11 indexed citations
19.
Ombuki-Berman, Beatrice, et al.. (2007). Waste collection vehicle routing problem with time windows using multi-objective genetic algorithms. Computational intelligence. 91–97. 29 indexed citations
20.
Ombuki-Berman, Beatrice, et al.. (2007). Dynamic vehicle routing using genetic algorithms. Applied Intelligence. 27(1). 89–99. 110 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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