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Konstantinos Liagkouras
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2020 – today
- 2023
- [j15]Konstantinos Liagkouras, Konstantinos Metaxiotis:
Sources of Uncertainty and Risk Quantification Methods in Supply Chain Management: A Literature Study. Oper. Res. Forum 4(4): 90 (2023) - 2022
- [j14]Konstantinos Liagkouras
, Kostas S. Metaxiotis, George A. Tsihrintzis:
Incorporating environmental and social considerations into the portfolio optimization process. Ann. Oper. Res. 316(2): 1493-1518 (2022) - 2021
- [j13]Konstantinos Liagkouras
Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions. Eur. J. Oper. Res. 292(3): 1019-1036 (2021)
2010 – 2019
- 2019
- [j12]Konstantinos Liagkouras, Konstantinos Metaxiotis:
Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem. Ann. Oper. Res. 272(1-2): 119-137 (2019) - [j11]Konstantinos Liagkouras:
A new three-dimensional encoding multiobjective evolutionary algorithm with application to the portfolio optimization problem. Knowl. Based Syst. 163: 186-203 (2019) - 2018
- [j10]Konstantinos Liagkouras
A new efficiently encoded multiobjective algorithm for the solution of the cardinality constrained portfolio optimization problem. Ann. Oper. Res. 267(1-2): 281-319 (2018) - [j9]Konstantinos Liagkouras, Kostas S. Metaxiotis:
Multi-period mean-variance fuzzy portfolio optimization model with transaction costs. Eng. Appl. Artif. Intell. 67: 260-269 (2018) - [j8]Konstantinos Liagkouras
Examining the effect of different configuration issues of the multiobjective evolutionary algorithms on the efficient frontier formulation for the constrained portfolio optimization problem. J. Oper. Res. Soc. 69(3): 416-438 (2018) - [j7]Konstantinos Liagkouras
Handling the complexities of the multi-constrained portfolio optimization problem with the support of a novel MOEA. J. Oper. Res. Soc. 69(10): 1609-1627 (2018) - 2017
- [j6]Konstantinos Liagkouras
Enhancing the performance of MOEAs: an experimental presentation of a new fitness guided mutation operator. J. Exp. Theor. Artif. Intell. 29(1): 91-131 (2017) - [j5]Konstantinos Liagkouras
An experimental analysis of a new two-stage crossover operator for multiobjective optimization. Soft Comput. 21(3): 721-751 (2017) - 2016
- [b1]Konstantinos Liagkouras:
Novel multiobjective evolutionary algorithm approaches with application in the constrained portfolio optimization. University of Piraeus, Greece, 2016 - 2015
- [j4]Konstantinos Liagkouras
An Experimental Analysis of a New Interval-Based Mutation Operator. Int. J. Comput. Intell. Appl. 14(3): 1550018:1-1550018:19 (2015) - [j3]Konstantinos Liagkouras
Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics. Int. J. Inf. Technol. Decis. Mak. 14(3): 535-564 (2015) - 2014
- [j2]Konstantinos Liagkouras
A new Probe Guided Mutation operator and its application for solving the cardinality constrained portfolio optimization problem. Expert Syst. Appl. 41(14): 6274-6290 (2014) - 2013
- [c3]Konstantinos Liagkouras
An Elitist Polynomial Mutation Operator for Improved Performance of MOEAs in Computer Networks. ICCCN 2013: 1-5 - [c2]Konstantinos Metaxiotis, Konstantinos Liagkouras
A fitness guided mutation operator for improved performance of MOEAs. ICECS 2013: 751-754 - 2012
- [j1]Konstantinos Metaxiotis, Konstantinos Liagkouras
Multiobjective Evolutionary Algorithms for Portfolio Management: A comprehensive literature review. Expert Syst. Appl. 39(14): 11685-11698 (2012) - [c1]Konstantinos Metaxiotis, Konstantinos Liagkouras:
A Comparative Study of Intelligent Techniques for Modern Portfolio Management. IJCCI 2012: 268-272
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