Hybridized Elephant Herding Optimization Algorithm for Constrained Optimization

  • Ivana Strumberger
  • Nebojsa Bacanin
  • Milan TubaEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 734)


This paper introduces hybridized elephant herding optimization algorithm (EHO) adopted for solving constrained optimization problems. EHO is one of the latest swarm intelligence metaheuristic and the implementation of the EHO for constrained optimization was not found in literature. In order to evaluate the performance of the hybridized EHO algorithm, we conducted tests on 13 standard constrained benchmark functions. To prove efficiency and robustness of the hybridized EHO, a comparative analysis with basic EHO implementation, as well as with other state-of-the-art algorithms, such as firefly algorithm, seeker optimization algorithm and self-adaptive penalty function genetic algorithm was performed. Experiments show that the hybridized EHO on average outperforms other algorithms used in comparative analysis.


Elephant herding optimization Swarm intelligence algorithms Metaheuristics Constrained optimization problems 



This research is supported by Ministry of Education, Science and Technological Development of Republic of Serbia, Grant No. III-44006.


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Ivana Strumberger
    • 1
  • Nebojsa Bacanin
    • 1
  • Milan Tuba
    • 2
    Email author
  1. 1.Faculty of Informatics and ComputingSingidunum UniversityBelgradeSerbia
  2. 2.Department of Technical SciencesState University of Novi PazarNovi PazarSerbia

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