Laëtitia Jourdan

2.8k total citations
71 papers, 1.2k citations indexed

About

Laëtitia Jourdan is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Industrial and Manufacturing Engineering. According to data from OpenAlex, Laëtitia Jourdan has authored 71 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 24 papers in Computational Theory and Mathematics and 21 papers in Industrial and Manufacturing Engineering. Recurrent topics in Laëtitia Jourdan's work include Metaheuristic Optimization Algorithms Research (24 papers), Advanced Multi-Objective Optimization Algorithms (22 papers) and Vehicle Routing Optimization Methods (14 papers). Laëtitia Jourdan is often cited by papers focused on Metaheuristic Optimization Algorithms Research (24 papers), Advanced Multi-Objective Optimization Algorithms (22 papers) and Vehicle Routing Optimization Methods (14 papers). Laëtitia Jourdan collaborates with scholars based in France, Spain and Netherlands. Laëtitia Jourdan's co-authors include Clarisse Dhaenens, Enrique Alba, El‐Ghazali Talbi, José García-Nieto, Arnaud Liefooghe, Matthieu Basseur, El‐Ghazali Talbi, Carlos A. Coello Coello, David Corne and Marie‐Éléonore Kessaci and has published in prestigious journals such as European Journal of Operational Research, IEEE Transactions on Knowledge and Data Engineering and Applied Soft Computing.

In The Last Decade

Laëtitia Jourdan

67 papers receiving 1.1k citations

Peers

Laëtitia Jourdan
El‐Ghazali Talbi France
Paola Festa Italy
Halife Kodaz Türkiye
Jérémie Dubois-Lacoste Belgium
Leslie Pérez Cáceres Chile
Julien Lepagnot France
Xinchao Zhao China
Liangjun Ke China
Ilhem Boussaïd Algeria
Georgios Dounias Greece
El‐Ghazali Talbi France
Laëtitia Jourdan
Citations per year, relative to Laëtitia Jourdan Laëtitia Jourdan (= 1×) peers El‐Ghazali Talbi

Countries citing papers authored by Laëtitia Jourdan

Since Specialization
Citations

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

Fields of papers citing papers by Laëtitia Jourdan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laëtitia Jourdan

This figure shows the co-authorship network connecting the top 25 collaborators of Laëtitia Jourdan. A scholar is included among the top collaborators of Laëtitia Jourdan 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 Laëtitia Jourdan. Laëtitia Jourdan 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.
José-García, Adán, et al.. (2025). Exhaustive biclustering driven by self-learning evolutionary approach for biomedical data. Computer Methods and Programs in Biomedicine. 269. 108846–108846.
2.
Golabi, Mahmoud, et al.. (2024). UAV path planning techniques: a survey. RAIRO. Operations research. 58(4). 2951–2989. 14 indexed citations
3.
Cattaruzza, Diego, et al.. (2023). Improving neighborhood exploration into MOEA/D framework to solve a bi‐objective routing problem. International Transactions in Operational Research. 32(1). 117–143. 1 indexed citations
4.
5.
Jacques, Julie, et al.. (2023). E-learning recommender system dataset. Data in Brief. 47. 108942–108942. 4 indexed citations
6.
Samouëlian, Vanessa, et al.. (2022). 2022-RA-1699-ESGO ERAS pathway for gynecological oncology – a pre-post implementation cohort with 1211 patients. International Journal of Gynecological Cancer. 32. A466–A466. 1 indexed citations
7.
Jacques, Julie, et al.. (2022). A Multi-Objective E-learning Recommender System at Mandarine Academy.. SPIRE - Sciences Po Institutional REpository. 1 indexed citations
8.
Doniec, Arnaud, et al.. (2022). Towards hybridization of multi-agent simulation and metaheuristics applied to selective deconstruction. HAL (Le Centre pour la Communication Scientifique Directe). 767–773.
9.
Jacques, Julie, et al.. (2020). A Biclustering Method for Heterogeneous and Temporal Medical Data. IEEE Transactions on Knowledge and Data Engineering. 34(2). 506–518. 14 indexed citations
10.
11.
Kessaci, Marie‐Éléonore, et al.. (2018). Survey and unification of local search techniques in metaheuristics for multi-objective combinatorial optimisation. Journal of Heuristics. 24(6). 853–877. 18 indexed citations
12.
Jourdan, Laëtitia, et al.. (2016). Decoder-based evolutionary algorithm for bi-objective just-in-time single-machine job-shop. 1–8. 2 indexed citations
13.
Dhaenens, Clarisse, Laëtitia Jourdan, & Marie‐Éléonore Kessaci. (2015). Learning and Intelligent Optimization. Lecture notes in computer science. 4 indexed citations
14.
Liefooghe, Arnaud, et al.. (2012). On optimizing a bi-objective flowshop scheduling problem in an uncertain environment. Computers & Mathematics with Applications. 64(12). 3747–3762. 15 indexed citations
15.
16.
Kessaci, Marie‐Éléonore, Laëtitia Jourdan, & Clarisse Dhaenens. (2010). A new distance measure based on the exchange operator for the HFF-AVRP. LillOA (Université de Lille (University Of Lille)). 1 indexed citations
17.
Liefooghe, Arnaud, Laëtitia Jourdan, & El‐Ghazali Talbi. (2010). A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO. European Journal of Operational Research. 209(2). 104–112. 34 indexed citations
18.
Liefooghe, Arnaud, Laëtitia Jourdan, & El‐Ghazali Talbi. (2009). Metaheuristics and cooperative approaches for the Bi-objective Ring Star Problem. Computers & Operations Research. 37(6). 1033–1044. 17 indexed citations
19.
García-Nieto, José, Enrique Alba, Laëtitia Jourdan, & El‐Ghazali Talbi. (2007). A comparison of PSO and GA approaches for gene selection and classification of microarray data. 427–427. 9 indexed citations
20.
Jourdan, Laëtitia, David Corne, Dragan Savić, & G. A. Walters. (2005). Hybridising Rule Induction and Multi-Objective Evolutionary Search for Optimising Water Distribution Systems. 434–439. 7 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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