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A Survey of Hyper-heuristics for Dynamic Optimization Problems

  • Teodoro Macias-EscobarEmail author
  • Bernabé Dorronsoro
  • Laura Cruz-Reyes
  • Nelson Rangel-Valdez
  • Claudia Gómez-Santillán
Chapter
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Part of the Studies in Computational Intelligence book series (SCI, volume 862)

Abstract

Dynamic optimization problems have attracted the attention of researchers due to their wide variety of challenges and their suitability for real-world problems. The application of hyper-heuristics to solve optimization problems is another area that has gained interest recently. These algorithms can apply a search space exploration method at different stages of the execution for finding high quality solutions. However, most of the proposed works using these methodologies do not focus on the development of hyper-heuristics for dynamic optimization problems. Despite that, they arise as very appropriate methods for dynamic problems, being highly responsive and able to quickly adapt to any possible changes in the problem environment. In this paper, we present a brief study of the most salient previously proposed hyper-heuristics to solve dynamic optimization problems, and classify them, taking into consideration the complexity of their low-level heuristics. Then, we identify some the most important research areas that have been vaguely explored in the Literature yet.

Keywords

Dynamic optimization Hyper-heuristics Dynamic optimization problems Low-level heuristics 

Notes

Acknowledgements

This work was supported by the project TecNM 6308.17-P and the following CONACyT projects; Consolidation National Lab under project 280712; Cátedras CONACyT under Project 3058; and CONACyT National Grant System under Grant 465554; Spanish MINECO and ERDF under contracts TIN2014-60844-R (SAVANT project) and RYC-2013-13355, and the University of Cadiz (contract PR2018-056).

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Teodoro Macias-Escobar
    • 1
    • 2
    Email author
  • Bernabé Dorronsoro
    • 2
  • Laura Cruz-Reyes
    • 3
  • Nelson Rangel-Valdez
    • 3
  • Claudia Gómez-Santillán
    • 3
  1. 1.Tecnológico Nacional de MéxicoInstituto Tecnológico de TijuanaTijuanaMexico
  2. 2.Universidad de CádizCadizSpain
  3. 3.Tecnológico Nacional de MéxicoInstituto Tecnológico de Ciudad MaderoCiudad MaderoMexico

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