Gregorio Toscano‐Pulido

1.9k total citations
41 papers, 718 citations indexed

About

Gregorio Toscano‐Pulido is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Ocean Engineering. According to data from OpenAlex, Gregorio Toscano‐Pulido has authored 41 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Computational Theory and Mathematics, 24 papers in Artificial Intelligence and 5 papers in Ocean Engineering. Recurrent topics in Gregorio Toscano‐Pulido's work include Advanced Multi-Objective Optimization Algorithms (29 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Evolutionary Algorithms and Applications (17 papers). Gregorio Toscano‐Pulido is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (29 papers), Metaheuristic Optimization Algorithms Research (20 papers) and Evolutionary Algorithms and Applications (17 papers). Gregorio Toscano‐Pulido collaborates with scholars based in Mexico, United States and Spain. Gregorio Toscano‐Pulido's co-authors include Carlos A. Coello Coello, Alan Diaz-Manríquez, Mario Garza-Fabre, Eduardo Rodríguez-Tello, Wilfrido Gómez‐Flores, Kalyanmoy Deb, Ricardo Landa Becerra, Proteek Chandan Roy, Oliver Schütze and Lewis C. Linker and has published in prestigious journals such as SHILAP Revista de lepidopterología, European Journal of Operational Research and IEEE Transactions on Evolutionary Computation.

In The Last Decade

Gregorio Toscano‐Pulido

38 papers receiving 690 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregorio Toscano‐Pulido Mexico 14 508 428 92 57 57 41 718
Saúl Zapotecas–Martínez Mexico 16 611 1.2× 551 1.3× 118 1.3× 83 1.5× 33 0.6× 52 827
Md Asafuddoula Australia 11 555 1.1× 564 1.3× 149 1.6× 74 1.3× 36 0.6× 18 798
Xilu Wang Germany 9 260 0.5× 300 0.7× 80 0.9× 56 1.0× 41 0.7× 24 587
Adriana Lara Mexico 11 660 1.3× 573 1.3× 112 1.2× 106 1.9× 40 0.7× 28 854
Yu Setoguchi Japan 8 703 1.4× 613 1.4× 183 2.0× 82 1.4× 45 0.8× 9 923
Lie Meng Pang China 9 267 0.5× 277 0.6× 69 0.8× 63 1.1× 37 0.6× 46 497
Tatsuya Okabe Germany 8 340 0.7× 349 0.8× 55 0.6× 80 1.4× 159 2.8× 12 757
Krishnendu Sanyal India 5 385 0.8× 374 0.9× 67 0.7× 55 1.0× 20 0.4× 6 544
Hu Zhang China 15 395 0.8× 469 1.1× 46 0.5× 37 0.6× 31 0.5× 46 684
Dan Guo China 5 540 1.1× 527 1.2× 131 1.4× 52 0.9× 64 1.1× 8 781

Countries citing papers authored by Gregorio Toscano‐Pulido

Since Specialization
Citations

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

Fields of papers citing papers by Gregorio Toscano‐Pulido

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregorio Toscano‐Pulido. 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 Gregorio Toscano‐Pulido. The network helps show where Gregorio Toscano‐Pulido may publish in the future.

Co-authorship network of co-authors of Gregorio Toscano‐Pulido

This figure shows the co-authorship network connecting the top 25 collaborators of Gregorio Toscano‐Pulido. A scholar is included among the top collaborators of Gregorio Toscano‐Pulido 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 Gregorio Toscano‐Pulido. Gregorio Toscano‐Pulido 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.
Toscano‐Pulido, Gregorio, et al.. (2025). Next-generation techniques for parameter reduction for BMP multiobjective optimization in watershed planning. Environmental Modelling & Software. 193. 106651–106651.
2.
Deb, Kalyanmoy, et al.. (2024). Leveraging innovization and transfer learning to optimize best management practices in large-scale watershed management. Environmental Modelling & Software. 180. 106161–106161. 3 indexed citations
3.
Becerra, Ricardo Landa, et al.. (2024). Optimization of Deep Neural Networks Using a Micro Genetic Algorithm. SHILAP Revista de lepidopterología. 5(4). 2651–2679. 1 indexed citations
4.
Toscano‐Pulido, Gregorio, et al.. (2023). Utilizing Innovization to Solve Large-Scale Multi-Objective Chesapeake Bay Watershed Problem. 1–8. 2 indexed citations
5.
Toscano‐Pulido, Gregorio, et al.. (2018). A COMPARATIVE STUDY OF NEIGHBORHOOD TOPOLOGIES FOR PARTICLE SWARM OPTIMIZERS. 152–159. 5 indexed citations
6.
Becerra, Ricardo Landa, et al.. (2018). Use of a goal-constraint-based approach for finding the region of interest in multi-objective problems. Journal of Heuristics. 25(1). 107–139. 4 indexed citations
7.
Rubio‐Loyola, Javier, et al.. (2017). Enhancing Metaheuristic-Based Online Embedding in Network Virtualization Environments. IEEE Transactions on Network and Service Management. 15(1). 200–216. 16 indexed citations
8.
Toscano‐Pulido, Gregorio & Kalyanmoy Deb. (2016). Study of the approximation of the fitness landscape and the ranking process of scalarizing functions for many-objective problems. 34. 4358–4365. 3 indexed citations
9.
Diaz-Manríquez, Alan, Gregorio Toscano‐Pulido, & Carlos A. Coello Coello. (2016). Comparison of metamodeling techniques in evolutionary algorithms. Soft Computing. 21(19). 5647–5663. 87 indexed citations
10.
Diaz-Manríquez, Alan, et al.. (2016). A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms. Computational Intelligence and Neuroscience. 2016. 1–14. 77 indexed citations
11.
Garza-Fabre, Mario, Eduardo Rodríguez-Tello, & Gregorio Toscano‐Pulido. (2014). Constraint-handling through multi-objective optimization: The hydrophobic-polar model for protein structure prediction. Computers & Operations Research. 53. 128–153. 15 indexed citations
12.
Garza-Fabre, Mario, Gregorio Toscano‐Pulido, & Eduardo Rodríguez-Tello. (2014). Multi-objectivization, fitness landscape transformation and search performance: A case of study on the hp model for protein structure prediction. European Journal of Operational Research. 243(2). 405–422. 14 indexed citations
13.
Diaz-Manríquez, Alan, Gregorio Toscano‐Pulido, & Ricardo Landa Becerra. (2013). On the use of a BSP Tree to create local surrogate models. 3. 2540–2547. 1 indexed citations
14.
Diaz-Manríquez, Alan, Gregorio Toscano‐Pulido, Carlos A. Coello Coello, & Ricardo Landa Becerra. (2013). A ranking method based on the R2 indicator for many-objective optimization. 1523–1530. 39 indexed citations
15.
Garza-Fabre, Mario, Gregorio Toscano‐Pulido, & Eduardo Rodríguez-Tello. (2012). Locality-based multiobjectivization for the HP model of protein structure prediction. 473–480. 12 indexed citations
16.
Diaz-Manríquez, Alan, Gregorio Toscano‐Pulido, & Wilfrido Gómez‐Flores. (2011). On the selection of surrogate models in evolutionary optimization algorithms. 2155–2162. 60 indexed citations
17.
Toscano‐Pulido, Gregorio, et al.. (2010). A Complete Closed-Form Solution to the Inverse Kinematics Problem for the P2Arm Manipulator Robot. 4. 372–377. 2 indexed citations
18.
Toscano‐Pulido, Gregorio, et al.. (2009). A New Object Path Planner for the Box Pushing Problem. 119–124. 7 indexed citations
19.
Schütze, Oliver, El‐Ghazali Talbi, Gregorio Toscano‐Pulido, Carlos A. Coello Coello, & Luis V. Santana‐Quintero. (2007). A Memetic PSO Algorithm for Scalar Optimization Problems. 128–134. 15 indexed citations
20.
Coello, Carlos A. Coello & Gregorio Toscano‐Pulido. (2001). Multiobjective optimization using a micro-genetic algorithm. Genetic and Evolutionary Computation Conference. 274–282. 129 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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