IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i18p2335-d639634.html
   My bibliography  Save this article

Review of Metaheuristics Inspired from the Animal Kingdom

Author

Listed:
  • Elena Niculina Dragoi

    (Faculty of Automatic Control and Computer Engineering, “Gheorghe Asachi” Technical University, Bld. Dimitrie Mangeron, No. 27, 700050 Iaşi, Romania
    Faculty of Chemical Engineering and Environmental Protection “Cristofor Simionescu”, “Gheorghe Asachi” Technical University, Bld. Dimitrie Mangeron, No. 73, 700050 Iaşi, Romania)

  • Vlad Dafinescu

    (Faculty of Chemical Engineering and Environmental Protection “Cristofor Simionescu”, “Gheorghe Asachi” Technical University, Bld. Dimitrie Mangeron, No. 73, 700050 Iaşi, Romania
    Emergency Hospital “Prof. Dr. N. Oblu”, Str. Ateneului No. 2, 700309 Iaşi, Romania)

Abstract

The search for powerful optimizers has led to the development of a multitude of metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom as a source of inspiration and performs an extensive, yet not exhaustive, review of the animal inspired metaheuristics proposed in the 2006–2021 period. The review is organized considering the biological classification of living things, with a breakdown of the simulated behavior mechanisms. The centralized data indicated that 61.6% of the animal-based algorithms are inspired from vertebrates and 38.4% from invertebrates. In addition, an analysis of the mechanisms used to ensure diversity was performed. The results obtained showed that the most frequently used mechanisms belong to the niching category.

Suggested Citation

  • Elena Niculina Dragoi & Vlad Dafinescu, 2021. "Review of Metaheuristics Inspired from the Animal Kingdom," Mathematics, MDPI, vol. 9(18), pages 1-52, September.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2335-:d:639634
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/18/2335/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/18/2335/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yi Cao & Xiangtao Li & Jianan Wang, 2013. "Opposition-Based Animal Migration Optimization," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, October.
    2. Alberto Luque-Chang & Erik Cuevas & Fernando Fausto & Daniel Zaldívar & Marco Pérez, 2018. "Social Spider Optimization Algorithm: Modifications, Applications, and Perspectives," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-29, December.
    3. Ikeda, Shintaro & Ooka, Ryozo, 2015. "Metaheuristic optimization methods for a comprehensive operating schedule of battery, thermal energy storage, and heat source in a building energy system," Applied Energy, Elsevier, vol. 151(C), pages 192-205.
    4. John Silberholz & Bruce Golden, 2010. "Comparison of Metaheuristics," International Series in Operations Research & Management Science, in: Michel Gendreau & Jean-Yves Potvin (ed.), Handbook of Metaheuristics, chapter 0, pages 625-640, Springer.
    5. E Emary & Hossam M Zawbaa, 2016. "Impact of Chaos Functions on Modern Swarm Optimizers," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-26, July.
    6. Erik Cuevas & Adrián González & Fernando Fausto & Daniel Zaldívar & Marco Pérez-Cisneros, 2015. "Multithreshold Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-25, August.
    7. 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.
    8. Stavros P. Adam & Stamatios-Aggelos N. Alexandropoulos & Panos M. Pardalos & Michael N. Vrahatis, 2019. "No Free Lunch Theorem: A Review," Springer Optimization and Its Applications, in: Ioannis C. Demetriou & Panos M. Pardalos (ed.), Approximation and Optimization, pages 57-82, Springer.
    9. Sioud, A. & Gagné, C., 2018. "Enhanced migrating birds optimization algorithm for the permutation flow shop problem with sequence dependent setup times," European Journal of Operational Research, Elsevier, vol. 264(1), pages 66-73.
    10. Fathy, Ahmed & Elaziz, Mohamed Abd & Sayed, Enas Taha & Olabi, A.G. & Rezk, Hegazy, 2019. "Optimal parameter identification of triple-junction photovoltaic panel based on enhanced moth search algorithm," Energy, Elsevier, vol. 188(C).
    11. Primitivo Díaz & Marco Pérez-Cisneros & Erik Cuevas & Omar Avalos & Jorge Gálvez & Salvador Hinojosa & Daniel Zaldivar, 2018. "An Improved Crow Search Algorithm Applied to Energy Problems," Energies, MDPI, vol. 11(3), pages 1-22, March.
    12. Lijin Wang & Yiwen Zhong, 2015. "Cuckoo Search Algorithm with Chaotic Maps," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-14, July.
    13. Dong Liu & Chunlei Liu & Qiang Fu & Tianxiao Li & Muhammad Imran Khan & Song Cui & Muhammad Abrar Faiz, 2018. "Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1325-1342, March.
    14. Millie Pant & Kusum Deep & Jagdish Chand Bansal & Kedar Nath Das & Atulya K. Nagar, 2018. "Soft computing for problem solving (SocProS 2015)," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(1), pages 1-1, February.
    15. Yanhui Che & Dengxu He, 2021. "A Hybrid Whale Optimization with Seagull Algorithm for Global Optimization Problems," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-31, January.
    16. Mohammad Ehteram & Hojat Karami & Saeed Farzin, 2018. "Reducing Irrigation Deficiencies Based Optimizing Model for Multi-Reservoir Systems Utilizing Spider Monkey Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(7), pages 2315-2334, May.
    17. Mingzhi Ma & Qifang Luo & Yongquan Zhou & Xin Chen & Liangliang Li, 2015. "An Improved Animal Migration Optimization Algorithm for Clustering Analysis," Discrete Dynamics in Nature and Society, Hindawi, vol. 2015, pages 1-12, January.
    18. S Kulluk, 2013. "A novel hybrid algorithm combining hunting search with harmony search algorithm for training neural networks," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(5), pages 748-761, May.
    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. Andrei Panteleev & Maria Karane, 2023. "Application of a Novel Multi-Agent Optimization Algorithm Based on PID Controllers in Stochastic Control Problems," Mathematics, MDPI, vol. 11(13), pages 1-21, June.
    2. Paweł Sokólski & Tomasz A. Rutkowski & Bartosz Ceran & Daria Złotecka & Dariusz Horla, 2022. "The Influence of Cooperation on the Operation of an MPC Controller Pair in a Nuclear Power Plant Turbine Generator Set," Energies, MDPI, vol. 15(18), pages 1-19, September.
    3. Florin Leon & Mircea Hulea & Marius Gavrilescu, 2022. "Preface to the Special Issue on “Advances in Artificial Intelligence: Models, Optimization, and Machine Learning”," Mathematics, MDPI, vol. 10(10), pages 1-4, May.
    4. Mosbeh R. Kaloop & Bishwajit Roy & Kuldeep Chaurasia & Sean-Mi Kim & Hee-Myung Jang & Jong-Wan Hu & Basem S. Abdelwahed, 2022. "Shear Strength Estimation of Reinforced Concrete Deep Beams Using a Novel Hybrid Metaheuristic Optimized SVR Models," Sustainability, MDPI, vol. 14(9), pages 1-21, April.

    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. Khalid Almutairi & Salem Algarni & Talal Alqahtani & Hossein Moayedi & Amir Mosavi, 2022. "A TLBO-Tuned Neural Processor for Predicting Heating Load in Residential Buildings," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    3. Kostić, Srđan & Vasović, Nebojša & Sunarić, Duško, 2015. "A new approach to grid search method in slope stability analysis using Box–Behnken statistical design," Applied Mathematics and Computation, Elsevier, vol. 256(C), pages 425-437.
    4. Emad M. Ahmed & Mokhtar Aly & Manar Mostafa & Hegazy Rezk & Hammad Alnuman & Waleed Alhosaini, 2022. "An Accurate Model for Bifacial Photovoltaic Panels," Sustainability, MDPI, vol. 15(1), pages 1-27, December.
    5. Papul Changmai & Sunil Deka & Shashank Kumar & Thanikanti Sudhakar Babu & Belqasem Aljafari & Benedetto Nastasi, 2022. "A Critical Review on the Estimation Techniques of the Solar PV Cell’s Unknown Parameters," Energies, MDPI, vol. 15(19), pages 1-20, September.
    6. Masoud Zahedi Vahid & Ziad M. Ali & Ebrahim Seifi Najmi & Abdollah Ahmadi & Foad H. Gandoman & Shady H. E. Abdel Aleem, 2021. "Optimal Allocation and Planning of Distributed Power Generation Resources in a Smart Distribution Network Using the Manta Ray Foraging Optimization Algorithm," Energies, MDPI, vol. 14(16), pages 1-25, August.
    7. Shahbaa I. Khaleel, 2023. "Building a Tool for Optimal Test Cases Selection using Artificial Intelligence Techniques," Technium, Technium Science, vol. 8(1), pages 1-11.
    8. 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.
    9. Jilong Zhang & Yuan Diao, 2024. "Hierarchical Learning-Enhanced Chaotic Crayfish Optimization Algorithm: Improving Extreme Learning Machine Diagnostics in Breast Cancer," Mathematics, MDPI, vol. 12(17), pages 1-26, August.
    10. 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.
    11. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    12. Shahbaa I. Khaleel, 2023. "Constructing a Tool for Software Regression Testing Based on Crow Search Method," Technium, Technium Science, vol. 8(1), pages 60-71.
    13. Olabi, A.G. & Wilberforce, Tabbi & Abdelkareem, Mohammad Ali, 2021. "Fuel cell application in the automotive industry and future perspective," Energy, Elsevier, vol. 214(C).
    14. Gallo, A.B. & Simões-Moreira, J.R. & Costa, H.K.M. & Santos, M.M. & Moutinho dos Santos, E., 2016. "Energy storage in the energy transition context: A technology review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 800-822.
    15. Alma Rodríguez & Marco Pérez-Cisneros & Julio C. Rosas-Caro & Carolina Del-Valle-Soto & Jorge Gálvez & Erik Cuevas, 2021. "Robust Clustering Routing Method for Wireless Sensor Networks Considering the Locust Search Scheme," Energies, MDPI, vol. 14(11), pages 1-19, May.
    16. Taslimi-Renani, Ehsan & Modiri-Delshad, Mostafa & Elias, Mohamad Fathi Mohamad & Rahim, Nasrudin Abd., 2016. "Development of an enhanced parametric model for wind turbine power curve," Applied Energy, Elsevier, vol. 177(C), pages 544-552.
    17. Drexl, Michael & Schneider, Michael, 2015. "A survey of variants and extensions of the location-routing problem," European Journal of Operational Research, Elsevier, vol. 241(2), pages 283-308.
    18. 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.
    19. Scioletti, Michael S. & Goodman, Johanna K. & Kohl, Paul A. & Newman, Alexandra M., 2016. "A physics-based integer-linear battery modeling paradigm," Applied Energy, Elsevier, vol. 176(C), pages 245-257.
    20. Almubaidin, Mohammad Abdullah Abid & Ahmed, Ali Najah & Malek, Marlinda Abdul & Mahmoud, Moamin A. & Sherif, Mohsen & El-Shafie, Ahmed, 2024. "Enhancing reservoir operations with charged system search (CSS) algorithm: Accounting for sediment accumulation and multiple scenarios," Agricultural Water Management, Elsevier, vol. 293(C).

    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:gam:jmathe:v:9:y:2021:i:18:p:2335-:d:639634. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.