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Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems

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  • Amit Kumar Bairwa
  • Sandeep Joshi
  • Dilbag Singh

Abstract

Optimization is a buzzword, whenever researchers think of engineering problems. This paper presents a new metaheuristic named dingo optimizer (DOX) which is motivated by the behavior of dingo ( Canis familiaris dingo ). The overall concept is to develop this method involving the collaborative and social behavior of dingoes. The developed algorithm is based on the hunting behavior of dingoes that includes exploration, encircling, and exploitation. All the above prey hunting steps are modeled mathematically and are implemented in the simulator to test the performance of the proposed algorithm. Comparative analyses are drawn among the proposed approach and grey wolf optimizer (GWO) and particle swarm optimizer (PSO). Some of the well-known test functions are used for the comparative study of this work. The results reveal that the dingo optimizer performed significantly better than other nature-inspired algorithms.

Suggested Citation

  • Amit Kumar Bairwa & Sandeep Joshi & Dilbag Singh, 2021. "Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-12, June.
    • Handle: RePEc:hin:jnlmpe:2571863
    DOI: 10.1155/2021/2571863
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    Cited by:

    1. Samson Oladayo Ayanlade & Funso Kehinde Ariyo & Abdulrasaq Jimoh & Kayode Timothy Akindeji & Adeleye Oluwaseye Adetunji & Emmanuel Idowu Ogunwole & Dolapo Eniola Owolabi, 2023. "Optimal Allocation of Photovoltaic Distributed Generations in Radial Distribution Networks," Sustainability, MDPI, vol. 15(18), pages 1-26, September.
    2. Mohammed Alkahtani & Mustufa Haider Abidi & Hamoud S. Bin Obaid & Osama Alotaik, 2023. "Modified Gannet Optimization Algorithm for Reducing System Operation Cost in Engine Parts Industry with Pooling Management and Transport Optimization," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    3. Dahu Li & Hongyu Zhou & Yuan Chen & Yue Zhou & Yuze Rao & Wei Yao, 2023. "A Frequency Support Approach for Hybrid Energy Systems Considering Energy Storage," Energies, MDPI, vol. 16(10), pages 1-16, May.
    4. Mohamed Abdel-Basset & Reda Mohamed & Victor Chang, 2021. "An Efficient Parameter Estimation Algorithm for Proton Exchange Membrane Fuel Cells," Energies, MDPI, vol. 14(21), pages 1-23, November.

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