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Firefly Swarm: Metaheuristic Swarm Intelligence Technique for Mathematical Optimization

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Data Management, Analytics and Innovation

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 839))

Abstract

In this paper, we briefly reviewed the firefly algorithm fundamentals and its experimentation with diverse applications, highlighting its performance in engineering research and industrial applications in specific to machinery extracting the features to confine the deformities.

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References

  1. Yang, X. S. (2010). Engineering optimization: An introduction with metaheuristic applications. John Wiley & Sons.

    Google Scholar 

  2. Blum, C., & Roli, A. (2003). Metaheuristics in combinatorial optimization: Overview and conceptual comparison. ACM Computing Surveys, 35(3), 268–308.

    Article  Google Scholar 

  3. Yagiura, M., & Ibaraki, T. (2001). On metaheuristic algorithms for combinatorial optimization problems. Systems and Computers in Japan, 32(3), 33–55.

    Article  Google Scholar 

  4. Yang, X. S. (2010). Firefly algorithm, stochastic test functions and design optimisation. International Journal of Bio-Inspired Computation, 2(2), 78. https://doi.org/10.1504/ijbic.2010.032124.

    Article  Google Scholar 

  5. Gheraibia, Y., & Moussaoui, A. (2013). Penguins search optimization algorithm (PeSOA). Lecture Notes in Computer Science, 222–231. https://doi.org/10.1007/978-3-642-38577-3_23.

  6. Senthilnath, J., Omkar, S. N., & Mani, V. (2011). Clustering using firefly algorithm: Performance study. Swarm and Evolutionary Computation, 1(3), 164–171. https://doi.org/10.1016/j.swevo.2011.06.003.

    Article  Google Scholar 

  7. Yang, X. S. (2008). Nature-inspired metaheuristic algorithms (2nd ed.). Luniver Press.

    Google Scholar 

  8. Kumar, R., Talukdar, F., Dey, N., & Balas, V. (2016). Quality factor optimization of spiral inductor using firefly algorithm and its application in amplifier. International Journal of Advanced Intelligence Paradigms.

    Google Scholar 

  9. Nayyar, A., & Singh, R. (2014). A comprehensive review of ant colony optimization (ACO) based energy-efficient routing protocols for wireless sensor networks. International Journal of Wireless Networks and Broadband Technologies (IJWNBT), 3(3), 33–55.

    Google Scholar 

  10. Nayyar, A., & Singh, R. (2016). Ant colony optimization—computational swarm intelligence technique. In 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom) (pp. 1493–1499). IEEE.

    Google Scholar 

  11. Nayyar, A., & Singh, R. (2017). Ant colony optimization (ACO) based routing protocols for wireless sensor networks (WSN): a survey. International Journal of Advanced Computer Science and Applications, 8, 148–155.

    Google Scholar 

  12. Basu, B., & Mahanti, G. K. (2011). Fire fly and artificial bees colony algorithm for synthesis of scanned and broadside linear array antenna. Progress in Electromagnetics Research B, 32, 169–190. https://doi.org/10.2528/pierb11053108.

    Article  Google Scholar 

  13. Zaman, M. A., & Abdul Matin, M. (2012). Nonuniformly spaced linear antenna array design using firefly algorithm. International Journal of Microwave Science and Technology, 2012, 1–8. https://doi.org/10.1155/2012/256759.

    Article  Google Scholar 

  14. Jati, G. K., & Suyanto. (2011). Evolutionary discrete firefly algorithm for travelling salesman problem. Lecture Notes in Computer Science, 393–403. https://doi.org/10.1007/978-3-642-23857-4_38.

  15. Palit, S., Sinha, S. N., Molla, M. A., Khanra, A., & Kule, M. (2011). A cryptanalytic attack on the knapsack cryptosystem using binary firefly algorithm. In 2011 2nd International Conference on Computer and Communication Technology (ICCCT-2011). https://doi.org/10.1109/iccct.2011.6075143.

  16. Sayadi, M. K., Ramezanian, R., & Ghaffari-Nasab, N. (2010). A discrete firefly meta-heuristic with local search for makespan minimization in permutation flow shop scheduling problems. International Journal of Industrial Engineering Computations, 1(1), 1–10. https://doi.org/10.5267/j.ijiec.2010.01.001.

    Article  Google Scholar 

  17. Kwiecień, J., & Filipowicz, B. (2014). Comparison of firefly and cockroach algorithms in selected discrete and combinatorial problems. Bulletin of the Polish Academy of Sciences Technical Sciences, 62(4). https://doi.org/10.2478/bpasts-2014-0087.

  18. Layeb, A., & Benayad, Z. (2014). A novel firefly algorithm based ant colony optimization for solving combinatorial optimization problems. International Journal of Computer Science and Applications, 11(2), 19–37.

    Google Scholar 

  19. Sharma, A., & Sehgal, S. (2016). Image segmentation using firefly algorithm. In 2016 International Conference on Information Technology (InCITe)—The Next Generation IT Summit on the Theme—Internet of Things: Connect Your Worlds. https://doi.org/10.1109/incite.2016.7857598.

  20. Bendjeghaba, O. (2014). Continuous firefly algorithm for optimal tuning of PID controller in AVR system. Journal of Electrical Engineering, 65(1). https://doi.org/10.2478/jee-2014-0006.

  21. Thelaidjia, T., Moussaoui, A., & Chenikher, S. (2014). Support vector machine based on firefly algorithm for bearing fault diagnosis. In International Conference of Modeling and Simulation (ICMS 14).

    Google Scholar 

  22. Hassanzadeh, T., & Meybodi, M. R. (2012). A new hybrid approach for data clustering using firefly algorithm and K-means. In The 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012). https://doi.org/10.1109/aisp.2012.6313708.

  23. Durbhaka, G. K., & Barani, S. (2016). Fault behaviour pattern analysis and recognition. In 2016 International Conference on Information Science (ICIS). https://doi.org/10.1109/infosci.2016.7845325.

  24. Durbhaka, G. K., & Selvaraj, B. (2016). Predictive maintenance for wind turbine diagnostics using vibration signal analysis based on collaborative recommendation approach. In 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI). https://doi.org/10.1109/icacci.2016.7732316.

  25. Massan, S.-R., Wagan, A. I., Shaikh, M. M., & Abro, R. (2015). Wind turbine micrositing by using the firefly algorithm. Applied Soft Computing, 27, 450–456. https://doi.org/10.1016/j.asoc.2014.09.048.

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Electronics and Control Engineering, Satyabhama University, Chennai, India

    Gopi Krishna Durbhaka & Barani Selvaraj

  2. Graduate School, Duy Tan University, Da Nang, Vietnam

    Anand Nayyar

Authors
  1. Gopi Krishna Durbhaka
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  2. Barani Selvaraj
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  3. Anand Nayyar
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Corresponding author

Correspondence to Gopi Krishna Durbhaka .

Editor information

Editors and Affiliations

  1. Department of Automatics and Applied Software, Aurel Vlaicu University of Arad, Arad, Romania

    Valentina Emilia Balas

  2. Adyogik Tantra Shikshan Sanstha’s IICMR, Pune, Maharashtra, India

    Neha Sharma

  3. Faculty of Engineering and Technology, A.K. Choudhury School of Information Technology, Kolkata, India

    Amlan Chakrabarti

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© 2019 Springer Nature Singapore Pte Ltd.

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Durbhaka, G.K., Selvaraj, B., Nayyar, A. (2019). Firefly Swarm: Metaheuristic Swarm Intelligence Technique for Mathematical Optimization. In: Balas, V., Sharma, N., Chakrabarti, A. (eds) Data Management, Analytics and Innovation. Advances in Intelligent Systems and Computing, vol 839. Springer, Singapore. https://doi.org/10.1007/978-981-13-1274-8_34

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  • DOI: https://doi.org/10.1007/978-981-13-1274-8_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-1273-1

  • Online ISBN: 978-981-13-1274-8

  • eBook Packages: EngineeringEngineering (R0)

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