IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v54y2017i3d10.1007_s12597-016-0291-4.html
   My bibliography  Save this article

Hybridizing gravitational search algorithm with real coded genetic algorithms for structural engineering design problem

Author

Listed:
  • Amarjeet Singh

    (Indian Institute of Technology Roorkee)

  • Kusum Deep

    (Indian Institute of Technology Roorkee)

Abstract

The focus of this paper is gravitational search algorithm which is a relatively new heuristics algorithm for function optimization. In order to improve the efficiency and reliability it was hybridized with real coded genetic algorithm and extensively applied to solve benchmarks problems available in literature. In the present paper, these hybridized variants are used to solve three constrained engineering design problem. The obtained results are compared with an extensively available results in literature. It is proved that the performance of one of the hybridized version outperform the remaining hybridized version as well as original gravitational search algorithm, in term of quality of solution and computation effort.

Suggested Citation

  • Amarjeet Singh & Kusum Deep, 2017. "Hybridizing gravitational search algorithm with real coded genetic algorithms for structural engineering design problem," OPSEARCH, Springer;Operational Research Society of India, vol. 54(3), pages 505-536, September.
    • Handle: RePEc:spr:opsear:v:54:y:2017:i:3:d:10.1007_s12597-016-0291-4
    DOI: 10.1007/s12597-016-0291-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-016-0291-4
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-016-0291-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Omran, Mahamed G.H. & Salman, Ayed, 2009. "Constrained optimization using CODEQ," Chaos, Solitons & Fractals, Elsevier, vol. 42(2), pages 662-668.
    2. Liu, Jianjun & Wu, Changzhi & Wu, Guoning & Wang, Xiangyu, 2015. "A novel differential search algorithm and applications for structure design," Applied Mathematics and Computation, Elsevier, vol. 268(C), pages 246-269.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chou, Jui-Sheng & Truong, Dinh-Nhat, 2021. "A novel metaheuristic optimizer inspired by behavior of jellyfish in ocean," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    2. Zhao, Ruxin & Wang, Yongli & Liu, Chang & Hu, Peng & Li, Yanchao & Li, Hao & Yuan, Chi, 2020. "Selfish herd optimizer with levy-flight distribution strategy for global optimization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 538(C).
    3. Hossein Moayedi & Amir Mosavi, 2021. "An Innovative Metaheuristic Strategy for Solar Energy Management through a Neural Networks Framework," Energies, MDPI, vol. 14(4), pages 1-18, February.
    4. Garg, Harish, 2016. "A hybrid PSO-GA algorithm for constrained optimization problems," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 292-305.
    5. Ali Aldrees, 2021. "Water management in Saudi Arabia: a case study of Makkah Al Mukarramah region," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(9), pages 13650-13666, September.
    6. Ridha, Hussein Mohammed & Hizam, Hashim & Gomes, Chandima & Heidari, Ali Asghar & Chen, Huiling & Ahmadipour, Masoud & Muhsen, Dhiaa Halboot & Alghrairi, Mokhalad, 2021. "Parameters extraction of three diode photovoltaic models using boosted LSHADE algorithm and Newton Raphson method," Energy, Elsevier, vol. 224(C).
    7. Hossein Moayedi & Amir Mosavi, 2021. "Electrical Power Prediction through a Combination of Multilayer Perceptron with Water Cycle Ant Lion and Satin Bowerbird Searching Optimizers," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    8. Yu, Qiang, 2021. "A decoupled wavelet approach for multiple physical flow fields of binary nanofluid in double-diffusive convection," Applied Mathematics and Computation, Elsevier, vol. 404(C).
    9. Yan Cao & Towhid Pourrostam & Yousef Zandi & Nebojša Denić & Bogdan Ćirković & Alireza Sadighi Agdas & Abdellatif Selmi & Vuk Vujović & Kittisak Jermsittiparsert & Momir Milic, 2021. "RETRACTED ARTICLE: Analyzing the energy performance of buildings by neuro-fuzzy logic based on different factors," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 17349-17373, December.
    10. Hossein Moayedi & Amir Mosavi, 2021. "Synthesizing Multi-Layer Perceptron Network with Ant Lion Biogeography-Based Dragonfly Algorithm Evolutionary Strategy Invasive Weed and League Champion Optimization Hybrid Algorithms in Predicting He," Sustainability, MDPI, vol. 13(6), pages 1-20, March.
    11. Tung L. Dang & Thi H. H. Huynh & Manh T. Nguyen, 2021. "Media attention and firm value: International evidence," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 865-894, September.
    12. Chen, Chengcheng & Wang, Xianchang & Yu, Helong & Wang, Mingjing & Chen, Huiling, 2021. "Dealing with multi-modality using synthesis of Moth-flame optimizer with sine cosine mechanisms," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 291-318.
    13. Hao Liu & Yue Wang & Liangping Tu & Guiyan Ding & Yuhan Hu, 2019. "A modified particle swarm optimization for large-scale numerical optimizations and engineering design problems," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2407-2433, August.
    14. Hossein Moayedi & Amir Mosavi, 2021. "Suggesting a Stochastic Fractal Search Paradigm in Combination with Artificial Neural Network for Early Prediction of Cooling Load in Residential Buildings," Energies, MDPI, vol. 14(6), pages 1-19, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:opsear:v:54:y:2017:i:3:d:10.1007_s12597-016-0291-4. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.