Slim Bechikh

3.5k total citations · 1 hit paper
79 papers, 2.2k citations indexed

About

Slim Bechikh is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems. According to data from OpenAlex, Slim Bechikh has authored 79 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Artificial Intelligence, 35 papers in Computational Theory and Mathematics and 20 papers in Information Systems. Recurrent topics in Slim Bechikh's work include Advanced Multi-Objective Optimization Algorithms (35 papers), Metaheuristic Optimization Algorithms Research (33 papers) and Evolutionary Algorithms and Applications (21 papers). Slim Bechikh is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (35 papers), Metaheuristic Optimization Algorithms Research (33 papers) and Evolutionary Algorithms and Applications (21 papers). Slim Bechikh collaborates with scholars based in Tunisia, United States and France. Slim Bechikh's co-authors include Lamjed Ben Saïd, Khaled Ghédira, Marouane Kessentini, Kalyanmoy Deb, Radhia Azzouz, Maha Elarbi, Mohamed Wiem Mkaouer, Ali Ouni, Abhishek Gupta and Yew-Soon Ong and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Slim Bechikh

73 papers receiving 2.1k citations

Hit Papers

Many-Objective Software Remodularization Using NSGA-III 2015 2026 2018 2022 2015 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Many-Objective Software Remodularization Using NSGA-III
    2015 191 citations Marouane Kessentini, Slim Bechikh et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Slim Bechikh Tunisia 24 1.1k 961 644 462 235 79 2.2k
Matej Črepinšek Slovenia 21 1.6k 1.5× 854 0.9× 294 0.5× 255 0.6× 202 0.9× 45 2.5k
Peter Gorm Larsen Denmark 21 554 0.5× 448 0.5× 349 0.5× 552 1.2× 249 1.1× 150 2.1k
Francisco Luna Spain 23 1.1k 1.0× 1.0k 1.1× 298 0.5× 131 0.3× 447 1.9× 89 2.4k
Johannes Bader Switzerland 11 1.6k 1.5× 1.8k 1.9× 209 0.3× 123 0.3× 175 0.7× 12 2.5k
Juan J. Durillo Spain 25 1.5k 1.3× 1.5k 1.5× 943 1.5× 265 0.6× 812 3.5× 44 3.2k
Xiaoyu Song United States 27 1.1k 1.0× 1.0k 1.1× 350 0.5× 236 0.5× 658 2.8× 271 2.9k
Zhiqiu Huang China 23 749 0.7× 203 0.2× 999 1.6× 367 0.8× 424 1.8× 241 2.1k
Boudewijn R. Haverkort Netherlands 24 432 0.4× 1.1k 1.1× 281 0.4× 633 1.4× 939 4.0× 176 2.6k
Andrea Bondavalli Italy 23 558 0.5× 243 0.3× 396 0.6× 557 1.2× 1.0k 4.4× 236 2.1k

Countries citing papers authored by Slim Bechikh

Since Specialization
Citations

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

Fields of papers citing papers by Slim Bechikh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Slim Bechikh

This figure shows the co-authorship network connecting the top 25 collaborators of Slim Bechikh. A scholar is included among the top collaborators of Slim Bechikh 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 Slim Bechikh. Slim Bechikh 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.
Elarbi, Maha, et al.. (2025). Deep crossover schemes for genetic algorithms: Investigations on the travel salesman problem. Swarm and Evolutionary Computation. 98. 102094–102094.
2.
Louati, Hassen, Ali Louati, Slim Bechikh, & Elham Kariri. (2024). Joint filter and channel pruning of convolutional neural networks as a bi-level optimization problem. Memetic Computing. 16(1). 71–90. 7 indexed citations
3.
4.
Louati, Hassen, Ali Louati, Slim Bechikh, & Elham Kariri. (2023). Embedding channel pruning within the CNN architecture design using a bi-level evolutionary approach. The Journal of Supercomputing. 79(14). 16118–16151. 3 indexed citations
5.
Bechikh, Slim, et al.. (2023). Imbalanced multi-label data classification as a bi-level optimization problem: application to miRNA-related diseases diagnosis. Neural Computing and Applications. 35(22). 16285–16303. 1 indexed citations
6.
Elarbi, Maha, et al.. (2022). Discretization-Based Feature Selection as a Bilevel Optimization Problem. IEEE Transactions on Evolutionary Computation. 27(4). 893–907. 14 indexed citations
7.
Louati, Hassen, Slim Bechikh, Ali Louati, Abdulaziz Aldaej, & Lamjed Ben Saïd. (2022). Joint design and compression of convolutional neural networks as a Bi-level optimization problem. Neural Computing and Applications. 34(17). 15007–15029. 9 indexed citations
8.
Dagdia, Zaineb Chelly, et al.. (2022). Many-objective optimization of wireless sensor network deployment. Evolutionary Intelligence. 17(2). 1047–1063. 7 indexed citations
9.
Bechikh, Slim, et al.. (2020). Solving Combinatorial Multi-Objective Bi-Level Optimization Problems Using Multiple Populations and Migration Schemes. IEEE Access. 8. 141674–141695. 21 indexed citations
10.
Elarbi, Maha, et al.. (2019). Approximating Complex Pareto Fronts With Predefined Normal-Boundary Intersection Directions. IEEE Transactions on Evolutionary Computation. 24(5). 809–823. 33 indexed citations
11.
Bechikh, Slim, et al.. (2019). Bi-level Decision-making Modeling for an Autonomous Driver Agent: Application in the Car-following Driving Behavior. Applied Artificial Intelligence. 33(13). 1157–1178. 8 indexed citations
12.
Bechikh, Slim, et al.. (2019). A Hybrid Evolutionary Algorithm with Heuristic Mutation for Multi-objective Bi-clustering. 2323–2330. 1 indexed citations
13.
Bechikh, Slim, et al.. (2019). Weighted-Features Construction as a Bi-level Problem. 23. 1604–1611. 4 indexed citations
14.
Bechikh, Slim, et al.. (2018). Anticipation model based on a modified fuzzy logic approach. IET Intelligent Transport Systems. 13(2). 330–339. 8 indexed citations
15.
Elarbi, Maha, Slim Bechikh, Abhishek Gupta, Lamjed Ben Saïd, & Yew-Soon Ong. (2017). A New Decomposition-Based NSGA-II for Many-Objective Optimization. IEEE Transactions on Systems Man and Cybernetics Systems. 48(7). 1191–1210. 221 indexed citations
16.
Datta, Rituparna, et al.. (2016). Recent Advances in Evolutionary Multi-objective Optimization. CERN Document Server (European Organization for Nuclear Research). 93 indexed citations
17.
Azzouz, Radhia, Slim Bechikh, & Lamjed Ben Saïd. (2015). A dynamic multi-objective evolutionary algorithm using a change severity-based adaptive population management strategy. Soft Computing. 21(4). 885–906. 128 indexed citations
18.
Kessentini, Marouane, et al.. (2014). MOMM: Multi-objective model merging. Journal of Systems and Software. 103. 423–439. 23 indexed citations
19.
Azzouz, Radhia, Slim Bechikh, & Lamjed Ben Saïd. (2014). A Multiple Reference Point-based evolutionary algorithm for dynamic multi-objective optimization with undetectable changes. 51. 3168–3175. 31 indexed citations
20.
Bechikh, Slim, et al.. (2013). On the Influence of the Number of Objectives in Evolutionary Autonomous Software Agent Testing. 2. 229–234. 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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