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Sine cosine grey wolf optimizer to solve engineering design problems

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Abstract

Balancing the exploration and exploitation in any nature-inspired optimization algorithm is an essential task, while solving the real-world global optimization problems. Therefore, the search agents of an algorithm always try to explore the unvisited domains of a search space in a balanced manner. The sine cosine algorithm (SCA) is a recent addition to the field of metaheuristics that finds the solution of an optimization problem using the behavior of sine and cosine functions. However, in some cases, the SCA skips the true solutions and trapped at sub-optimal solutions. These problems lead to the premature convergence, which is harmful in determining the global optima. Therefore, in order to alleviate the above-mentioned issues, the present study aims to establish a comparatively better synergy between exploration and exploitation in the SCA. In this direction, firstly, the exploration ability of the SCA is improved by integrating the social and cognitive component, and secondly, the balance between exploration and exploitation is maintained through the grey wolf optimizer (GWO). The proposed algorithm is named as SC-GWO. For the performance evaluation, a well-known set of benchmark problems and engineering test problems are taken. The dimension of benchmark test problems is varied from 30 to 100 to observe the robustness of the SC-GWO on scalability of problems. In the paper, the SC-GWO is also used to determine the optimal setting for overcurrent relays. The analysis of obtained numerical results and its comparison with other metaheuristic algorithms demonstrate the superior ability of the proposed SC-GWO.

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Authors and Affiliations

  1. Institute for Mega Construction, Korea University, Seoul, 02841, South Korea

    Shubham Gupta

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Informetrics Research Group, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hossein Moayedi

  4. Faculty of Civil Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Hossein Moayedi

  5. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Loke Kok Foong

  6. Faculty of Civil Engineering, Duy Tan University, Da Nang, 550000, Vietnam

    Loke Kok Foong

  7. Department of Computer Science and Engineering, Islamic University of Science and Technology Awantipora, Awantipora, J & K, 192122, India

    Assif Assad

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  1. Shubham Gupta
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Gupta, S., Deep, K., Moayedi, H. et al. Sine cosine grey wolf optimizer to solve engineering design problems. Engineering with Computers 37, 3123–3149 (2021). https://doi.org/10.1007/s00366-020-00996-y

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