Hernán Aguirre

2.6k total citations
97 papers, 993 citations indexed

About

Hernán Aguirre is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Hernán Aguirre has authored 97 papers receiving a total of 993 indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Artificial Intelligence, 61 papers in Computational Theory and Mathematics and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Hernán Aguirre's work include Advanced Multi-Objective Optimization Algorithms (60 papers), Metaheuristic Optimization Algorithms Research (57 papers) and Evolutionary Algorithms and Applications (45 papers). Hernán Aguirre is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (60 papers), Metaheuristic Optimization Algorithms Research (57 papers) and Evolutionary Algorithms and Applications (45 papers). Hernán Aguirre collaborates with scholars based in Japan, France and Mexico. Hernán Aguirre's co-authors include Kiyoshi Tanaka, Wei Tan, Hiroyuki Satō, Chee Seng Chan, Carlos A. Coello Coello, Saúl Zapotecas–Martínez, Fabio Daolio, Arnaud Liefooghe, Sebástien Vérel and Youhei Akimoto and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and European Journal of Operational Research.

In The Last Decade

Hernán Aguirre

90 papers receiving 968 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hernán Aguirre Japan 18 552 525 190 121 79 97 993
Anas A. Hadi Egypt 12 990 1.8× 558 1.1× 143 0.8× 36 0.3× 57 0.7× 20 1.4k
Sheng-Uei Guan China 20 640 1.2× 181 0.3× 326 1.7× 29 0.2× 48 0.6× 117 1.2k
S. Kobayashi Japan 11 520 0.9× 494 0.9× 44 0.2× 93 0.8× 12 0.2× 35 845
Peter Vrancx Belgium 12 328 0.6× 119 0.2× 68 0.4× 130 1.1× 24 0.3× 50 768
I. Grondman Netherlands 6 349 0.6× 186 0.4× 74 0.4× 39 0.3× 25 0.3× 8 841
Salvador Hinojosa Mexico 16 377 0.7× 137 0.3× 281 1.5× 23 0.2× 27 0.3× 36 825
Gabriel Dulac-Arnold United Kingdom 6 594 1.1× 83 0.2× 158 0.8× 78 0.6× 30 0.4× 8 1.0k
Antonio Rodríguez-Díaz Mexico 15 792 1.4× 341 0.6× 102 0.5× 204 1.7× 15 0.2× 46 1.5k
Meng Hiot Lim Singapore 14 666 1.2× 333 0.6× 104 0.5× 69 0.6× 29 0.4× 28 1.1k
Beatrice Ombuki-Berman Canada 14 398 0.7× 257 0.5× 58 0.3× 44 0.4× 8 0.1× 55 772

Countries citing papers authored by Hernán Aguirre

Since Specialization
Citations

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

Fields of papers citing papers by Hernán Aguirre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hernán Aguirre. 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 Hernán Aguirre. The network helps show where Hernán Aguirre may publish in the future.

Co-authorship network of co-authors of Hernán Aguirre

This figure shows the co-authorship network connecting the top 25 collaborators of Hernán Aguirre. A scholar is included among the top collaborators of Hernán Aguirre 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 Hernán Aguirre. Hernán Aguirre 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.
Aguirre, Hernán, et al.. (2024). Repeated $\epsilon$-Sampling for Many-Objective Optimization. 1–8.
2.
Derbel, Bilel, et al.. (2019). Surrogate-assisted multiobjective optimization based on decomposition. Proceedings of the Genetic and Evolutionary Computation Conference. 507–515. 6 indexed citations
3.
Fonlupt, Cyril, et al.. (2019). Fitness landscapes analysis and adaptive algorithms design for traffic lights optimization on SIALAC benchmark. Applied Soft Computing. 85. 105869–105869. 2 indexed citations
4.
Zapotecas–Martínez, Saúl, Carlos A. Coello Coello, Hernán Aguirre, & Kiyoshi Tanaka. (2018). A Review of Features and Limitations of Existing Scalable Multiobjective Test Suites. IEEE Transactions on Evolutionary Computation. 23(1). 130–142. 45 indexed citations
5.
Aguirre, Hernán, Saúl Zapotecas–Martínez, Arnaud Liefooghe, et al.. (2018). Pareto dominance-based MOEAs on problems with difficult pareto set topologies. Proceedings of the Genetic and Evolutionary Computation Conference Companion. 189–190. 3 indexed citations
6.
Tan, Wei, Chee Seng Chan, Hernán Aguirre, & Kiyoshi Tanaka. (2017). ArtGAN: Artwork Synthesis with Conditional Categorial GANs.. arXiv (Cornell University). 11 indexed citations
7.
Aguirre, Hernán, et al.. (2017). Closed state model for understanding the dynamics of MOEAs. Proceedings of the Genetic and Evolutionary Computation Conference. 609–616. 2 indexed citations
9.
Satō, Hiroyuki, Hernán Aguirre, & Kiyoshi Tanaka. (2011). Improved S-CDAs using crossover controlling the number of crossed genes for many-objective optimization. 753–760. 14 indexed citations
10.
Satō, Hiroyuki, Hernán Aguirre, & Kiyoshi Tanaka. (2010). Effects of MOEA Temporally Switching Pareto Partial Dominance on Many-objective 0/1 Knapsack Problems. Transactions of the Japanese Society for Artificial Intelligence. 25(2). 320–331. 3 indexed citations
12.
Satō, Hiroyuki, Hernán Aguirre, & Kiyoshi Tanaka. (2007). Local Dominance Including Control of Dominance Area of Solutions in MOEAs. 2632. 310–317. 7 indexed citations
13.
Aguirre, Hernán, et al.. (2004). Inter-block evaluation method to further reduce evaluation numbers in GA-based image halftoning technique. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 87(10). 2722–2731.
14.
Aguirre, Hernán & Kiyoshi Tanaka. (2003). A Study on the Behavior of Genetic Algorithms on NK-Landscapes: Effects of Selection Drift, Mutation, and Recombination. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 86(9). 2270–2279. 11 indexed citations
15.
Aguirre, Hernán, et al.. (2003). Accelerated halftoning technique using improved genetic algorithm with tiny populations. 4. 905–910. 1 indexed citations
16.
Aguirre, Hernán, et al.. (2002). Multi-Level Image Halftoning Technique with Genetic Algorithms. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 85(8). 1892–1897.
17.
Aguirre, Hernán, et al.. (2001). Increasing the robustness of distributed genetic algorithms by parallel cooperative-competitive genetic operators. Genetic and Evolutionary Computation Conference. 195–202. 4 indexed citations
18.
Aguirre, Hernán. (2001). Simultaneous Halftone Image Generation with Improved Multiobjective Genetic Algorithm. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 84(8). 1869–1882.
19.
Aguirre, Hernán. (2000). Accelerated Image Halftoning Technique Using Improved Genetic Algorithm. IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences. 83(8). 1566–1574. 1 indexed citations
20.
Aguirre, Hernán, et al.. (1999). Cooperative Crossover and Mutation Operators in Genetic Algorithms.. Genetic and Evolutionary Computation Conference. 772. 772. 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.

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