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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

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  • K. Liagkouras

    (University of Piraeus)

  • K. Metaxiotis

    (University of Piraeus)

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.

Suggested Citation

  • K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    • Handle: RePEc:spr:annopr:v:272:y:2019:i:1:d:10.1007_s10479-018-2876-1
    DOI: 10.1007/s10479-018-2876-1
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    1. Ron Bird & Mark Tippett, 1986. "Note---Naive Diversification and Portfolio Risk---A Note," Management Science, INFORMS, vol. 32(2), pages 244-251, February.
    2. Liu, Yong-Jun & Zhang, Wei-Guo, 2013. "Fuzzy portfolio optimization model under real constraints," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 704-711.
    3. Deb, Kalyanmoy & Tiwari, Santosh, 2008. "Omni-optimizer: A generic evolutionary algorithm for single and multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1062-1087, March.
    4. Chen, Wei, 2015. "Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 125-139.
    5. Gupta, Pankaj & Mittal, Garima & Mehlawat, Mukesh Kumar, 2013. "Expected value multiobjective portfolio rebalancing model with fuzzy parameters," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 190-203.
    6. Zhang, Wei-Guo & Liu, Yong-Jun & Xu, Wei-Jun, 2012. "A possibilistic mean-semivariance-entropy model for multi-period portfolio selection with transaction costs," European Journal of Operational Research, Elsevier, vol. 222(2), pages 341-349.
    7. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    8. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    9. Adam Krzemienowski & Sylwia Szymczyk, 2016. "Portfolio optimization with a copula-based extension of conditional value-at-risk," Annals of Operations Research, Springer, vol. 237(1), pages 219-236, February.
    10. Toker Doganoglu & Christoph Hartz & Stefan Mittnik, 2007. "Portfolio optimization when risk factors are conditionally varying and heavy tailed," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 333-354, May.
    11. Clara Calvo & Carlos Ivorra & Vicente Liern, 2016. "Fuzzy portfolio selection with non-financial goals: exploring the efficient frontier," Annals of Operations Research, Springer, vol. 245(1), pages 31-46, October.
    12. Alois Geyer & Michael Hanke & Alex Weissensteiner, 2009. "A stochastic programming approach for multi-period portfolio optimization," Computational Management Science, Springer, vol. 6(2), pages 187-208, May.
    13. Laila Messaoudi & Belaid Aouni & Abdelwaheb Rebai, 2017. "Fuzzy chance-constrained goal programming model for multi-attribute financial portfolio selection," Annals of Operations Research, Springer, vol. 251(1), pages 193-204, April.
    14. Li, Xiang & Shou, Biying & Qin, Zhongfeng, 2012. "An expected regret minimization portfolio selection model," European Journal of Operational Research, Elsevier, vol. 218(2), pages 484-492.
    15. K. Liagkouras & K. Metaxiotis, 2015. "Efficient Portfolio Construction with the Use of Multiobjective Evolutionary Algorithms: Best Practices and Performance Metrics," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 14(03), pages 535-564.
    16. John L. Evans & Stephen H. Archer, 1968. "Diversification And The Reduction Of Dispersion: An Empirical Analysis," Journal of Finance, American Finance Association, vol. 23(5), pages 761-767, December.
    17. Johnson, K. H. & Shannon, D. S., 1974. "A note on diversification and the reduction of dispersion," Journal of Financial Economics, Elsevier, vol. 1(4), pages 365-372, December.
    18. Frank Fabozzi & Dashan Huang & Guofu Zhou, 2010. "Robust portfolios: contributions from operations research and finance," Annals of Operations Research, Springer, vol. 176(1), pages 191-220, April.
    19. Jennings, Edward H., 1971. "An Empirical Analysis of Some Aspects of Common Stock Diversification," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 6(2), pages 797-813, March.
    20. Zhang, Wei-Guo & Zhang, Xi-Li & Xiao, Wei-Lin, 2009. "Portfolio selection under possibilistic mean-variance utility and a SMO algorithm," European Journal of Operational Research, Elsevier, vol. 197(2), pages 693-700, September.
    21. Zenios, Stavros A. & Holmer, Martin R. & McKendall, Raymond & Vassiadou-Zeniou, Christiana, 1998. "Dynamic models for fixed-income portfolio management under uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 22(10), pages 1517-1541, August.
    22. Simone Brands & David R. Gallagher, 2005. "Portfolio selection, diversification and fund‐of‐funds: a note," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 45(2), pages 185-197, July.
    23. Tang, Gordon Y. N., 2004. "How efficient is naive portfolio diversification? an educational note," Omega, Elsevier, vol. 32(2), pages 155-160, April.
    24. Rudolf, Markus & Ziemba, William T., 2004. "Intertemporal surplus management," Journal of Economic Dynamics and Control, Elsevier, vol. 28(5), pages 975-990, February.
    25. John M. Mulvey & Hercules Vladimirou, 1992. "Stochastic Network Programming for Financial Planning Problems," Management Science, INFORMS, vol. 38(11), pages 1642-1664, November.
    26. Adam Krzemienowski, 2009. "Risk preference modeling with conditional average: an application to portfolio optimization," Annals of Operations Research, Springer, vol. 165(1), pages 67-95, January.
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    Cited by:

    1. Liagkouras, Konstantinos & Metaxiotis, Konstantinos, 2021. "Improving multi-objective algorithms performance by emulating behaviors from the human social analogue in candidate solutions," European Journal of Operational Research, Elsevier, vol. 292(3), pages 1019-1036.
    2. K. Liagkouras & K. Metaxiotis & G. Tsihrintzis, 2022. "Incorporating environmental and social considerations into the portfolio optimization process," Annals of Operations Research, Springer, vol. 316(2), pages 1493-1518, September.

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