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Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization

Author

Listed:
  • Carlos Segura

    (Área de Computación)

  • Carlos A. Coello Coello

    (CINVESTAV-IPN)

  • Gara Miranda

    (Universidad de La Laguna)

  • Coromoto León

    (Universidad de La Laguna)

Abstract

In recent decades, several multi-objective evolutionary algorithms have been successfully applied to a wide variety of multi-objective optimization problems. Along the way, several new concepts, paradigms and methods have emerged. Additionally, some authors have claimed that the application of multi-objective approaches might be useful even in single-objective optimization. Thus, several guidelines for solving single-objective optimization problems using multi-objective methods have been proposed. This paper offers an updated survey of the main methods that allow the use of multi-objective schemes for single-objective optimization. In addition, several open topics and some possible paths of future work in this area are identified.

Suggested Citation

  • Carlos Segura & Carlos A. Coello Coello & Gara Miranda & Coromoto León, 2016. "Using multi-objective evolutionary algorithms for single-objective constrained and unconstrained optimization," Annals of Operations Research, Springer, vol. 240(1), pages 217-250, May.
    • Handle: RePEc:spr:annopr:v:240:y:2016:i:1:d:10.1007_s10479-015-2017-z
    DOI: 10.1007/s10479-015-2017-z
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    References listed on IDEAS

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    1. Garza-Fabre, Mario & Toscano-Pulido, Gregorio & Rodriguez-Tello, Eduardo, 2015. "Multi-objectivization, fitness landscape transformation and search performance: A case of study on the hp model for protein structure prediction," European Journal of Operational Research, Elsevier, vol. 243(2), pages 405-422.
    2. Eduardo Segredo & Carlos Segura & Coromoto León, 2014. "Memetic algorithms and hyperheuristics applied to a multiobjectivised two-dimensional packing problem," Journal of Global Optimization, Springer, vol. 58(4), pages 769-794, April.
    3. Lochtefeld, Darrell F. & Ciarallo, Frank W., 2015. "Multi-objectivization Via Decomposition: An analysis of helper-objectives and complete decomposition," European Journal of Operational Research, Elsevier, vol. 243(2), pages 395-404.
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    Cited by:

    1. Ji, Bin & Zhang, Binqiao & Yu, Samson S. & Zhang, Dezhi & Yuan, Xiaohui, 2021. "An enhanced Borg algorithmic framework for solving the hydro-thermal-wind Co-scheduling problem," Energy, Elsevier, vol. 218(C).
    2. Gabriele Eichfelder & Kathrin Klamroth & Julia Niebling, 2021. "Nonconvex constrained optimization by a filtering branch and bound," Journal of Global Optimization, Springer, vol. 80(1), pages 31-61, May.
    3. Han, Xiaojuan & Liu, Dahe & Liu, Jian & Kong, Lingda, 2017. "Sensitivity analysis of acquisition granularity of photovoltaic output power to capacity configuration of energy storage systems," Applied Energy, Elsevier, vol. 203(C), pages 794-807.
    4. Mohammed Mahrach & Gara Miranda & Coromoto León & Eduardo Segredo, 2020. "Comparison between Single and Multi-Objective Evolutionary Algorithms to Solve the Knapsack Problem and the Travelling Salesman Problem," Mathematics, MDPI, vol. 8(11), pages 1-23, November.
    5. Gloria Milena Vargas Gil & Lucas Lima Rodrigues & Roberto S. Inomoto & Alfeu J. Sguarezi & Renato Machado Monaro, 2019. "Weighted-PSO Applied to Tune Sliding Mode Plus PI Controller Applied to a Boost Converter in a PV System," Energies, MDPI, vol. 12(5), pages 1-18, March.
    6. Adeel, Muhammad & Hassan, Ahmad Kamal & Sher, Hadeed Ahmed & Murtaza, Ali Faisal, 2021. "A grade point average assessment of analytical and numerical methods for parameter extraction of a practical PV device," Renewable and Sustainable Energy Reviews, Elsevier, vol. 142(C).
    7. Fernanda Nakano Kazama & Aluizio Fausto Ribeiro Araujo & Paulo Barros Correia & Elaine Guerrero-Peña, 2021. "Constraint-guided evolutionary algorithm for solving the winner determination problem," Journal of Heuristics, Springer, vol. 27(6), pages 1111-1150, December.

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