K. Liagkouras

727 total citations
23 papers, 487 citations indexed

About

K. Liagkouras is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, K. Liagkouras has authored 23 papers receiving a total of 487 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computational Theory and Mathematics, 13 papers in Artificial Intelligence and 9 papers in Management Science and Operations Research. Recurrent topics in K. Liagkouras's work include Advanced Multi-Objective Optimization Algorithms (16 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Evolutionary Algorithms and Applications (8 papers). K. Liagkouras is often cited by papers focused on Advanced Multi-Objective Optimization Algorithms (16 papers), Metaheuristic Optimization Algorithms Research (13 papers) and Evolutionary Algorithms and Applications (8 papers). K. Liagkouras collaborates with scholars based in Greece. K. Liagkouras's co-authors include Kostas Metaxiotis and George A. Tsihrintzis and has published in prestigious journals such as European Journal of Operational Research, Expert Systems with Applications and Journal of the Operational Research Society.

In The Last Decade

K. Liagkouras

22 papers receiving 465 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
K. Liagkouras Greece 11 326 176 145 120 73 23 487
Dietmar Maringer Switzerland 12 425 1.3× 136 0.8× 137 0.9× 289 2.4× 63 0.9× 34 657
Jianjun Gao China 15 380 1.2× 57 0.3× 65 0.4× 307 2.6× 47 0.6× 66 692
Hamid Reza Golmakani Iran 11 251 0.8× 36 0.2× 52 0.4× 98 0.8× 67 0.9× 23 562
Zhaolin Hu China 8 230 0.7× 69 0.4× 59 0.4× 36 0.3× 32 0.4× 20 377
Jorge Navarro Mexico 14 396 1.2× 287 1.6× 208 1.4× 39 0.3× 15 0.2× 35 560
Horand I. Gassmann Canada 10 236 0.7× 70 0.4× 36 0.2× 40 0.3× 66 0.9× 19 478
Markus Hirschberger Germany 10 366 1.1× 68 0.4× 30 0.2× 229 1.9× 65 0.9× 14 561
Csaba I. Fábián Hungary 10 297 0.9× 53 0.3× 23 0.2× 147 1.2× 40 0.5× 22 401
Romy Shioda Canada 7 150 0.5× 63 0.4× 63 0.4× 45 0.4× 27 0.4× 7 416

Countries citing papers authored by K. Liagkouras

Since Specialization
Citations

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

Fields of papers citing papers by K. Liagkouras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Liagkouras

This figure shows the co-authorship network connecting the top 25 collaborators of K. Liagkouras. A scholar is included among the top collaborators of K. Liagkouras 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 K. Liagkouras. K. Liagkouras 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.
Liagkouras, K., et al.. (2025). A Hybrid Long Short-Term Memory with a Sentiment Analysis System for Stock Market Forecasting. Electronics. 14(14). 2753–2753.
2.
Liagkouras, K., et al.. (2023). Sources of Uncertainty and Risk Quantification Methods in Supply Chain Management: A Literature Study. Operations Research Forum. 4(4). 1 indexed citations
3.
Liagkouras, K., Kostas Metaxiotis, & George A. Tsihrintzis. (2020). Incorporating environmental and social considerations into the portfolio optimization process. Annals of Operations Research. 316(2). 1493–1518. 52 indexed citations
4.
Liagkouras, K., et al.. (2020). Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions. European Journal of Operational Research. 292(3). 1019–1036. 4 indexed citations
5.
Liagkouras, K.. (2018). A new three-dimensional encoding multiobjective evolutionary algorithm with application to the portfolio optimization problem. Knowledge-Based Systems. 163. 186–203. 37 indexed citations
6.
7.
Liagkouras, K. & Kostas Metaxiotis. (2017). Multi-period mean–variance fuzzy portfolio optimization model with transaction costs. Engineering Applications of Artificial Intelligence. 67. 260–269. 61 indexed citations
8.
Liagkouras, K., et al.. (2017). The Current State of ERP Systems in Banking Sector. 3(1). 23–23. 2 indexed citations
9.
Liagkouras, K. & Kostas Metaxiotis. (2017). Handling the complexities of the multi-constrained portfolio optimization problem with the support of a novel MOEA. Journal of the Operational Research Society. 69(10). 1609–1627. 15 indexed citations
10.
Liagkouras, K. & Kostas Metaxiotis. (2016). A new probe guided mutation operator for more efficient exploration of the search space: an experimental analysis. International Journal of Operational Research. 25(2). 212–212. 3 indexed citations
11.
Liagkouras, K. & Kostas Metaxiotis. (2016). A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem. Annals of Operations Research. 267(1-2). 281–319. 32 indexed citations
12.
Liagkouras, K. & Kostas Metaxiotis. (2015). An Experimental Analysis of a New Interval-Based Mutation Operator. International Journal of Computational Intelligence and Applications. 14(3). 1550018–1550018. 3 indexed citations
13.
Liagkouras, K., et al.. (2015). Advanced Technologies And Algorithms For Efficient Portfolio Selection. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
14.
Liagkouras, K. & Kostas Metaxiotis. (2015). Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics. International Journal of Information Technology & Decision Making. 14(3). 535–564. 32 indexed citations
15.
Liagkouras, K. & Kostas Metaxiotis. (2015). An experimental analysis of a new two-stage crossover operator for multiobjective optimization. Soft Computing. 21(3). 721–751. 10 indexed citations
16.
Liagkouras, K. & Kostas Metaxiotis. (2014). A new Probe Guided Mutation operator and its application for solving the cardinality constrained portfolio optimization problem. Expert Systems with Applications. 41(14). 6274–6290. 39 indexed citations
17.
Metaxiotis, Kostas & K. Liagkouras. (2014). An Expert System Designed To Be Used With Moeas For Efficient Portfolio Selection. Zenodo (CERN European Organization for Nuclear Research). 8(2). 295–301. 1 indexed citations
18.
Metaxiotis, Kostas & K. Liagkouras. (2013). A fitness guided mutation operator for improved performance of MOEAs. 751–754. 4 indexed citations
19.
Liagkouras, K. & Kostas Metaxiotis. (2013). The Constrained Mean-Semivariance Portfolio Optimization Problem with the Support of a Novel Multiobjective Evolutionary Algorithm. Journal of Software Engineering and Applications. 6(7). 22–29. 6 indexed citations
20.
Metaxiotis, Kostas & K. Liagkouras. (2012). Multiobjective Evolutionary Algorithms for Portfolio Management: A comprehensive literature review. Expert Systems with Applications. 39(14). 11685–11698. 134 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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2026