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Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem

  • S.I.: Advances in Theoretical and Applied Combinatorial Optimization
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Abstract

This paper examines the incorporation of useful information extracted from the evolutionary process, in order to improve algorithm performance. In order to achieve this objective, we introduce an efficient method of extracting and utilizing valuable information from the evolutionary process. Finally, this information is utilized for optimizing the search process. The proposed algorithm is compared with the NSGAII for solving some real-world instances of the fuzzy portfolio optimization problem. The proposed algorithm outperforms the NSGAII for all examined test instances.

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  1. Decision Support Systems Laboratory, Department of Informatics, University of Piraeus, 80, Karaoli and Dimitriou Str., 18534, Piraeus, Greece

    K. Liagkouras & K. Metaxiotis

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  1. K. Liagkouras
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  2. K. Metaxiotis
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Correspondence to K. Liagkouras.

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Liagkouras, K., Metaxiotis, K. 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, 119–137 (2019). https://doi.org/10.1007/s10479-018-2876-1

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