Review on Elephant Herding Optimization Algorithm Performance in Solving Optimization Problems

  • Authors

    • Saman M. Almufti computer science
    • Renas R. Asaad computer science
    • Baraa W. Salim computer science
    https://doi.org/10.14419/ijet.v7i4.28473

    Received date: March 17, 2019

    Accepted date: March 26, 2019

    Published date: May 11, 2019

  • Metaheuristic, Elephant Herding Optimization (EHO), Optimization, Evolutionary Algorithms, Swarm Intelligences.

  • Abstract

    Elephant Herding optimization algorithm (EHO) is a metaheuristic swarm based search algorithm, which is used to solve various optimization problems. EHO can be used to solve as benchmark problems, Services Selection in QoS-Aware Web Service Compositions, Energy-Based Localization, PID controller tuning, Appliance Scheduling in Smart Grid identification and other problems. The algorithm is deducted from the behavior of elephant groups in the wild. Were elephants live in a clan with a leader matriarch (Female elephant), while the male elephants separate from the group when they reach adulthood. This is used in the algorithm in two parts. First, the clan updating mechanism. Second, the separation mechanism.

    In this paper, a review of the Elephant Herding optimization algorithm is presented. Moreover, a comparison of results of EHO compared to other optimization algorithm is presented based on previous work results. In the experimental results section, the result of EHO will be compared with the U-Turning Ant Colony Optimization Algorithm (U-TACO) in solving Traveling Salesman Problem (TSP), which is based on Ant Colony Optimization (ACO).

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  • How to Cite

    M. Almufti, S., R. Asaad, R., & W. Salim, B. (2019). Review on Elephant Herding Optimization Algorithm Performance in Solving Optimization Problems. International Journal of Engineering and Technology, 7(4), 6109-6114. https://doi.org/10.14419/ijet.v7i4.28473