IDEAS home Printed from https://ideas.repec.org/a/eee/matcom/v185y2021icp17-46.html
   My bibliography  Save this article

Nature-inspired approach: An enhanced whale optimization algorithm for global optimization

Author

Listed:
  • Yan, Zheping
  • Zhang, Jinzhong
  • Zeng, Jia
  • Tang, Jialing

Abstract

The whale optimization algorithm is based on the bubble-net attacking behavior of humpback whales and simulates encircling prey, bubble-net attacking and searching for prey to obtain the global optimal solution. However, the basic whale optimization algorithm has the disadvantage of search stagnation, easily falls into a local optimum, has slow convergence speed and has low calculation accuracy. The Lévy flight strategy is beneficial for expanding the search range and prevents the algorithm from falling into a local optimum, which enhances the global search ability. The ranking-based mutation operator can increase the selection probability and accelerate the convergence speed to enhance the local search ability. To overcome these shortcomings and avoid premature convergence, the Lévy flight strategy and the ranking-based mutation operator are added to the whale optimization algorithm. In this paper, an enhanced whale optimization algorithm is proposed, which realizes complementary advantages to balance exploration and exploitation. Eighteen benchmark test functions and five structural engineering design problems are used to verify the robustness and overall optimization performance of the enhanced whale optimization algorithm. The experimental results show that the enhanced whale optimization algorithm is an effective and feasible method that has a fast convergence speed, high calculation accuracy, strong robustness and stability.

Suggested Citation

  • Yan, Zheping & Zhang, Jinzhong & Zeng, Jia & Tang, Jialing, 2021. "Nature-inspired approach: An enhanced whale optimization algorithm for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 185(C), pages 17-46.
  • Handle: RePEc:eee:matcom:v:185:y:2021:i:c:p:17-46
    DOI: 10.1016/j.matcom.2020.12.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378475420304638
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.matcom.2020.12.008?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. Zhang, Yun & Liu, Yongguo & Li, Jieting & Zhu, Jiajing & Yang, Changhong & Yang, Wen & Wen, Chuanbiao, 2020. "WOCDA: A whale optimization based community detection algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 539(C).
    2. Luo, Qifang & Yang, Xiao & Zhou, Yongquan, 2019. "Nature-inspired approach: An enhanced moth swarm algorithm for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 57-92.
    3. Mohammadi, Babak & Mehdizadeh, Saeid, 2020. "Modeling daily reference evapotranspiration via a novel approach based on support vector regression coupled with whale optimization algorithm," Agricultural Water Management, Elsevier, vol. 237(C).
    4. Fister, Iztok & Iglesias, Andres & Galvez, Akemi & Del Ser, Javier & Osaba, Eneko & Fister, Iztok & Perc, Matjaž & Slavinec, Mitja, 2019. "Novelty search for global optimization," Applied Mathematics and Computation, Elsevier, vol. 347(C), pages 865-881.
    5. Yuting Lu & Yongquan Zhou & Xiuli Wu, 2017. "A Hybrid Lightning Search Algorithm-Simplex Method for Global Optimization," Discrete Dynamics in Nature and Society, Hindawi, vol. 2017, pages 1-23, July.
    6. Fister, Iztok & Perc, Matjaž & Kamal, Salahuddin M. & Fister, Iztok, 2015. "A review of chaos-based firefly algorithms: Perspectives and research challenges," Applied Mathematics and Computation, Elsevier, vol. 252(C), pages 155-165.
    7. Zhiming Li & Yongquan Zhou & Sen Zhang & Junmin Song, 2016. "Lévy-Flight Moth-Flame Algorithm for Function Optimization and Engineering Design Problems," Mathematical Problems in Engineering, Hindawi, vol. 2016, pages 1-22, August.
    8. Du, Wenbo & Zhang, Mingyuan & Ying, Wen & Perc, Matjaž & Tang, Ke & Cao, Xianbin & Wu, Dapeng, 2018. "The networked evolutionary algorithm: A network science perspective," Applied Mathematics and Computation, Elsevier, vol. 338(C), pages 33-43.
    9. Garg, Harish, 2016. "A hybrid PSO-GA algorithm for constrained optimization problems," Applied Mathematics and Computation, Elsevier, vol. 274(C), pages 292-305.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hu, Gang & Du, Bo & Li, Huinan & Wang, Xupeng, 2022. "Quadratic interpolation boosted black widow spider-inspired optimization algorithm with wavelet mutation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 200(C), pages 428-467.
    2. Juan Li & Qing An & Hong Lei & Qian Deng & Gai-Ge Wang, 2022. "Survey of Lévy Flight-Based Metaheuristics for Optimization," Mathematics, MDPI, vol. 10(15), pages 1-27, August.
    3. Deng, Huaijun & Liu, Linna & Fang, Jianyin & Qu, Boyang & Huang, Quanzhen, 2023. "A novel improved whale optimization algorithm for optimization problems with multi-strategy and hybrid algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 205(C), pages 794-817.
    4. Liu, Jianxun & Shi, Jinfei & Hao, Fei & Dai, Min, 2022. "A reinforced exploration mechanism whale optimization algorithm for continuous optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 23-48.
    5. Li, Maodong & Xu, Guanghui & Lai, Qiang & Chen, Jie, 2022. "A chaotic strategy-based quadratic Opposition-Based Learning adaptive variable-speed whale optimization algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 193(C), pages 71-99.
    6. Theogan Logan Pillay & Akshay Kumar Saha, 2024. "A Review of Metaheuristic Optimization Techniques for Effective Energy Conservation in Buildings," Energies, MDPI, vol. 17(7), pages 1-36, March.
    7. Changfu Tong & Hongfei Hou & Hexiang Zheng & Ying Wang & Jin Liu, 2024. "A Coupled Model for Forecasting Spatiotemporal Variability of Regional Drought in the Mu Us Sandy Land Using a Meta-Heuristic Algorithm," Land, MDPI, vol. 13(11), pages 1-22, October.
    8. Kang, Helei & Liu, Renyun & Yao, Yifei & Yu, Fanhua, 2023. "Improved Harris hawks optimization for non-convex function optimization and design optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 204(C), pages 619-639.
    9. Jinzhong Zhang & Tan Zhang & Gang Zhang & Min Kong, 2023. "Parameter optimization of PID controller based on an enhanced whale optimization algorithm for AVR system," Operational Research, Springer, vol. 23(3), pages 1-26, September.
    10. Zhang, Jinzhong & Zhang, Gang & Kong, Min & Zhang, Tan & Wang, Duansong & Chen, Rui, 2023. "CWOA: A novel complex-valued encoding whale optimization algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 207(C), pages 151-188.
    11. He, Bohao & Jia, Biying & Zhao, Yanghe & Wang, Xu & Wei, Mao & Dietzel, Ranae, 2022. "Estimate soil moisture of maize by combining support vector machine and chaotic whale optimization algorithm," Agricultural Water Management, Elsevier, vol. 267(C).

    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. Mehmood, Ammara & Raja, Muhammad Asif Zahoor & Ninness, Brett, 2024. "Design of fractional-order hammerstein control auto-regressive model for heat exchanger system identification: Treatise on fuzzy-evolutionary computing," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    2. Kutlu Onay, Funda & Aydemı̇r, Salih Berkan, 2022. "Chaotic hunger games search optimization algorithm for global optimization and engineering problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 514-536.
    3. Yu, Caiyang & Cai, Zhennao & Ye, Xiaojia & Wang, Mingjing & Zhao, Xuehua & Liang, Guoxi & Chen, Huiling & Li, Chengye, 2020. "Quantum-like mutation-induced dragonfly-inspired optimization approach," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 178(C), pages 259-289.
    4. Hamdy M. Ahmed & Mahmoud M. El-Borai & Hassan M. El-Owaidy & Ahmed S. Ghanem, 2019. "Existence Solution and Controllability of Sobolev Type Delay Nonlinear Fractional Integro-Differential System," Mathematics, MDPI, vol. 7(1), pages 1-14, January.
    5. Qian, Qian & Chao, Xiangrui & Feng, Hairong, 2023. "Internal or external control? How to respond to credit risk contagion in complex enterprises network," International Review of Financial Analysis, Elsevier, vol. 87(C).
    6. Ivona Brajević & Jelena Ignjatović, 2019. "An upgraded firefly algorithm with feasibility-based rules for constrained engineering optimization problems," Journal of Intelligent Manufacturing, Springer, vol. 30(6), pages 2545-2574, August.
    7. Wang, Jianwei & Xu, Wenshu & Chen, Wei & Yu, Fengyuan & He, Jialu, 2021. "Information sharing can suppress the spread of epidemics: Voluntary vaccination game on two-layer networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 583(C).
    8. Zhou, Quan & Zhang, Wei & Cash, Scott & Olatunbosun, Oluremi & Xu, Hongming & Lu, Guoxiang, 2017. "Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization," Applied Energy, Elsevier, vol. 189(C), pages 588-601.
    9. Zhou, Hanmi & Ma, Linshuang & Niu, Xiaoli & Xiang, Youzhen & Chen, Jiageng & Su, Yumin & Li, Jichen & Lu, Sibo & Chen, Cheng & Wu, Qi, 2024. "A novel hybrid model combined with ensemble embedded feature selection method for estimating reference evapotranspiration in the North China Plain," Agricultural Water Management, Elsevier, vol. 296(C).
    10. Manish Kumar & Anuradha Kumari & Daniel Prakash Kushwaha & Pravendra Kumar & Anurag Malik & Rawshan Ali & Alban Kuriqi, 2020. "Estimation of Daily Stage–Discharge Relationship by Using Data-Driven Techniques of a Perennial River, India," Sustainability, MDPI, vol. 12(19), pages 1-21, September.
    11. Yassin Belkourchia & Mohamed Zeriab Es-Sadek & Lahcen Azrar, 2023. "New Hybrid Perturbed Projected Gradient and Simulated Annealing Algorithms for Global Optimization," Journal of Optimization Theory and Applications, Springer, vol. 197(2), pages 438-475, May.
    12. Babak Mohammadi & Farshad Ahmadi & Saeid Mehdizadeh & Yiqing Guan & Quoc Bao Pham & Nguyen Thi Thuy Linh & Doan Quang Tri, 2020. "Developing Novel Robust Models to Improve the Accuracy of Daily Streamflow Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(10), pages 3387-3409, August.
    13. Touqeer Ahmed Jumani & Mohd Wazir Mustafa & Nawaf N. Hamadneh & Samer H. Atawneh & Madihah Md. Rasid & Nayyar Hussain Mirjat & Muhammad Akram Bhayo & Ilyas Khan, 2020. "Computational Intelligence-Based Optimization Methods for Power Quality and Dynamic Response Enhancement of ac Microgrids," Energies, MDPI, vol. 13(16), pages 1-22, August.
    14. Li, Chao & Zhai, Rongrong & Yang, Yongping & Patchigolla, Kumar & Oakey, John E. & Turner, Peter, 2019. "Annual performance analysis and optimization of a solar tower aided coal-fired power plant," Applied Energy, Elsevier, vol. 237(C), pages 440-456.
    15. Brayan A. Atoccsa & David W. Puma & Daygord Mendoza & Estefany Urday & Cristhian Ronceros & Modesto T. Palma, 2024. "Optimization of Ampacity in High-Voltage Underground Cables with Thermal Backfill Using Dynamic PSO and Adaptive Strategies," Energies, MDPI, vol. 17(5), pages 1-19, February.
    16. Luo, Qifang & Yang, Xiao & Zhou, Yongquan, 2019. "Nature-inspired approach: An enhanced moth swarm algorithm for global optimization," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 159(C), pages 57-92.
    17. Máximo Méndez & Mariano Frutos & Fabio Miguel & Ricardo Aguasca-Colomo, 2020. "TOPSIS Decision on Approximate Pareto Fronts by Using Evolutionary Algorithms: Application to an Engineering Design Problem," Mathematics, MDPI, vol. 8(11), pages 1-27, November.
    18. Hadeel E. Khairan & Salah L. Zubaidi & Mustafa Al-Mukhtar & Anmar Dulaimi & Hussein Al-Bugharbee & Furat A. Al-Faraj & Hussein Mohammed Ridha, 2023. "Assessing the Potential of Hybrid-Based Metaheuristic Algorithms Integrated with ANNs for Accurate Reference Evapotranspiration Forecasting," Sustainability, MDPI, vol. 15(19), pages 1-19, September.
    19. Elbeltagi, Ahmed & Deng, Jinsong & Wang, Ke & Malik, Anurag & Maroufpoor, Saman, 2020. "Modeling long-term dynamics of crop evapotranspiration using deep learning in a semi-arid environment," Agricultural Water Management, Elsevier, vol. 241(C).
    20. Sujata Dash & Ajith Abraham & Ashish Kr Luhach & Jolanta Mizera-Pietraszko & Joel JPC Rodrigues, 2020. "Hybrid chaotic firefly decision making model for Parkinson’s disease diagnosis," International Journal of Distributed Sensor Networks, , vol. 16(1), pages 15501477198, January.

    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:eee:matcom:v:185:y:2021:i:c:p:17-46. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/mathematics-and-computers-in-simulation/ .

    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.