Hybrid metaheuristic algorithms: Past, present, and future

T. O. Ting*, Xin She Yang, Shi Cheng, Kaizhu Huang

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

178 Citations (Scopus)


Hybrid algorithms play a prominent role in improving the search capability of algorithms. Hybridization aims to combine the advantages of each algorithm to form a hybrid algorithm, while simultaneously trying to minimize any substantial disadvantage. In general, the outcome of hybridization can usually make some improvements in terms of either computational speed or accuracy. This chapter surveys recent advances in the area of hybridizing different algorithms. Based on this survey, some crucial recommendations are suggested for further development of hybrid algorithms.

Original languageEnglish
Title of host publicationStudies in Computational Intelligence
PublisherSpringer Verlag
Number of pages13
Publication statusPublished - 2015

Publication series

NameStudies in Computational Intelligence
ISSN (Print)1860-949X


  • Bio-inspired
  • Diversity
  • Evolutionary algorithms
  • Hybrid algorithms
  • Metaheuristics
  • Nature-inspired algorithms


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