Francisco Luna

4.0k total citations · 1 hit paper
89 papers, 2.4k citations indexed

About

Francisco Luna is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Francisco Luna has authored 89 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computational Theory and Mathematics, 36 papers in Artificial Intelligence and 30 papers in Electrical and Electronic Engineering. Recurrent topics in Francisco Luna's work include Advanced Multi-Objective Optimization Algorithms (38 papers), Metaheuristic Optimization Algorithms Research (31 papers) and Evolutionary Algorithms and Applications (21 papers). Francisco Luna is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (38 papers), Metaheuristic Optimization Algorithms Research (31 papers) and Evolutionary Algorithms and Applications (21 papers). Francisco Luna collaborates with scholars based in Spain, Uruguay and Argentina. Francisco Luna's co-authors include Antonio J. Nebro, Enrique Alba, Juan J. Durillo, Carlos A. Coello Coello, Bernabè Dorronsoro, José García-Nieto, Juan F. Valenzuela‐Valdés, Francisco Chicano, Andreas Beham and Pablo Padilla and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Francisco Luna

87 papers receiving 2.4k citations

Hit Papers

SMPSO: A new PSO-based me... 2009 2026 2014 2020 2009 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Francisco Luna Spain 23 1.1k 1.0k 447 415 298 89 2.4k
Matej Črepinšek Slovenia 21 1.6k 1.5× 854 0.8× 202 0.5× 211 0.5× 294 1.0× 45 2.5k
Juan J. Durillo Spain 25 1.5k 1.4× 1.5k 1.4× 812 1.8× 294 0.7× 943 3.2× 44 3.2k
Lamjed Ben Saïd Tunisia 23 1.0k 1.0× 882 0.9× 283 0.6× 162 0.4× 206 0.7× 176 2.3k
Viviane Grunert da Fonseca Portugal 3 1.6k 1.4× 2.0k 1.9× 198 0.4× 261 0.6× 195 0.7× 5 3.1k
Shih-Hsi Liu United States 14 1.3k 1.2× 717 0.7× 173 0.4× 196 0.5× 151 0.5× 40 2.0k
Manuel López‐Ibáñez United Kingdom 24 1.5k 1.4× 1.2k 1.1× 257 0.6× 269 0.6× 122 0.4× 84 3.0k
Ahamad Tajudin Khader Malaysia 25 1.7k 1.6× 544 0.5× 312 0.7× 345 0.8× 334 1.1× 66 3.0k
Bernabè Dorronsoro Spain 23 993 0.9× 718 0.7× 817 1.8× 276 0.7× 471 1.6× 110 2.2k
Slim Bechikh Tunisia 24 1.1k 1.0× 961 0.9× 235 0.5× 118 0.3× 644 2.2× 79 2.2k

Countries citing papers authored by Francisco Luna

Since Specialization
Citations

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

Fields of papers citing papers by Francisco Luna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Francisco Luna

This figure shows the co-authorship network connecting the top 25 collaborators of Francisco Luna. A scholar is included among the top collaborators of Francisco Luna 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 Francisco Luna. Francisco Luna 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
2.
Luna, Francisco, et al.. (2024). Landscape-enabled algorithmic design for the cell switch-off problem in 5G ultra-dense networks. Engineering Optimization. 57(1). 309–331. 1 indexed citations
3.
Luna, Francisco, et al.. (2023). Designing problem-specific operators for solving the Cell Switch-Off problem in ultra-dense 5G networks with hybrid MOEAs. Swarm and Evolutionary Computation. 78. 101290–101290. 9 indexed citations
4.
Nebro, Antonio J., et al.. (2022). Is NSGA-II Ready for Large-Scale Multi-Objective Optimization?. Mathematical and Computational Applications. 27(6). 103–103. 14 indexed citations
5.
Nesmachnow, Sergio, et al.. (2020). Optimizing household energy planning in smart cities: A multiobjective approach. Zenodo (CERN European Organization for Nuclear Research).
6.
Valenzuela‐Valdés, Juan F., et al.. (2020). Detection and Mitigation of DoS and DDoS Attacks in IoT-Based Stateful SDN: An Experimental Approach. Sensors. 20(3). 816–816. 107 indexed citations
7.
Nesmachnow, Sergio, et al.. (2020). Optimizing household energy planning in smart cities: A multiobjective approach. SHILAP Revista de lepidopterología. 6 indexed citations
8.
Palomares‐Caballero, Ángel, Antonio Alex‐Amor, Juan F. Valenzuela‐Valdés, Francisco Luna, & Pablo Padilla. (2019). Phase Shifter for Millimeter-Wave Frequency Range Based on Glide Symmetric Structures. Repositorio Institucional de la Universidad de Málaga (University of Málaga). 2 indexed citations
9.
Luna, Francisco, et al.. (2019). A robust approach to the cell switch-off problem in 5G ultradense networks. Institutional Repository of the University of Granada (University of Granada). 1 indexed citations
10.
Luna, Francisco, et al.. (2018). Addressing the 5G Cell Switch-off Problem with a Multi-objective Cellular Genetic Algorithm. 422–426. 11 indexed citations
11.
Alba, Enrique, et al.. (2016). Solving optimization problems using a hybrid systolic search on GPU plus CPU. Soft Computing. 21(12). 3227–3245. 9 indexed citations
12.
Luna, Francisco & Pedro Isasi. (2012). Multi-objective metaheuristics for multi-disciplinary engineering applications. Engineering Optimization. 44(3). 241–242. 4 indexed citations
13.
Nebro, Antonio J., Juan J. Durillo, José García-Nieto, et al.. (2009). SMPSO: A new PSO-based metaheuristic for multi-objective optimization. 66–73. 475 indexed citations breakdown →
14.
Durillo, Juan J., Antonio J. Nebro, Francisco Luna, & Enrique Alba. (2008). A study of master-slave approaches to parallelize NSGA-II. Proceedings - IEEE International Parallel and Distributed Processing Symposium. 1–8. 51 indexed citations
15.
Alba, Enrique, Francisco Luna, & Antonio J. Nebro. (2004). Advances in parallel heterogeneous genetic algorithms for continuous optimization. International Journal of Applied Mathematics and Computer Science. 14(3). 317–333. 13 indexed citations
16.
Luna, Francisco. (2004). Neli Zaitegi: equipos directivos : en busca de su identidad. Cuadernos de pedagogía. 40–44. 1 indexed citations
17.
Alba, Enrique, Francisco Luna, Antonio J. Nebro, & José M. Troya. (2004). Parallel heterogeneous genetic algorithms for continuous optimization. Parallel Computing. 30(5-6). 699–719. 42 indexed citations
18.
Nebro, Antonio J., Enrique Alba, Francisco Luna, & José M. Troya. (2002). NET as a Platform for Implementing Concurrent Objects (Research Note). 125–130. 2 indexed citations
19.
Luna, Francisco, et al.. (2002). Comunidades de aprendizaje. Cuadernos de pedagogía. 40–41. 90 indexed citations
20.
Luna, Francisco, et al.. (1998). CP "Ramón Bako" de Vitoria-Gasteiz: Una comunidad de aprendizaje. Cuadernos de pedagogía. 36–44. 2 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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