Skip to main content

2018 | OriginalPaper | Buchkapitel

13. Moth-Flame Optimization (MFO) Algorithm

verfasst von : Mahdi Bahrami, Omid Bozorg-Haddad, Xuefeng Chu

Erschienen in: Advanced Optimization by Nature-Inspired Algorithms

Verlag: Springer Singapore

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

This chapter introduces the Moth-Flame Optimization (MFO) algorithm, along with its applications and variations. The basic steps of the algorithm are explained in detail and a flowchart is represented. In order to better understand the algorithm, a pseudocode of the MFO is also included.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literatur
Zurück zum Zitat Allam, D., Yousri, D. A., & Eteiba, M. B. (2016). Parameters extraction of the three diode model for the multi-crystalline solar cell/module using Moth-Flame Optimization Algorithm. Energy Conversion and Management, 123, 535–548. Allam, D., Yousri, D. A., & Eteiba, M. B. (2016). Parameters extraction of the three diode model for the multi-crystalline solar cell/module using Moth-Flame Optimization Algorithm. Energy Conversion and Management, 123, 535–548.
Zurück zum Zitat Bentouati, B., Chaib, L., & Chettih, S. (2016). Optimal Power Flow using the Moth Flam Optimizer: A case study of the Algerian power system. Indonesian Journal of Electrical Engineering and Computer Science, 1(3), 431–445. Bentouati, B., Chaib, L., & Chettih, S. (2016). Optimal Power Flow using the Moth Flam Optimizer: A case study of the Algerian power system. Indonesian Journal of Electrical Engineering and Computer Science, 1(3), 431–445.
Zurück zum Zitat Bhesdadiya, R. H., Trivedi, I. N., Jangir, P., Kumar, A., Jangir, N., & Totlani, R. (2016, August 12–13). A novel hybrid approach particle swarm optimizer with moth flame optimizer algorithm. In International Conference on Computer, Communication and Computational Sciences (ICCCCS), Advances in Intelligent Systems and Computing. Ajmer, India. Bhesdadiya, R. H., Trivedi, I. N., Jangir, P., Kumar, A., Jangir, N., & Totlani, R. (2016, August 12–13). A novel hybrid approach particle swarm optimizer with moth flame optimizer algorithm. In International Conference on Computer, Communication and Computational Sciences (ICCCCS), Advances in Intelligent Systems and Computing. Ajmer, India.
Zurück zum Zitat Buch, H., Trivedi, I. N., & Jangir, P. (2017). Moth flame optimization to solve optimal power flow with non-parametric statistical evaluation validation. Cogent Engineering, 4(1). Buch, H., Trivedi, I. N., & Jangir, P. (2017). Moth flame optimization to solve optimal power flow with non-parametric statistical evaluation validation. Cogent Engineering, 4(1).
Zurück zum Zitat Ceylan, O. (2016, November 3–5). Harmonic elimination of multilevel inverters by moth-flame optimization algorithm. In International Symposium on Industrial Electronics (INDEL). Republic of Srpska, Bosnia and Herzegovina: IEEE. Ceylan, O. (2016, November 3–5). Harmonic elimination of multilevel inverters by moth-flame optimization algorithm. In International Symposium on Industrial Electronics (INDEL). Republic of Srpska, Bosnia and Herzegovina: IEEE.
Zurück zum Zitat Frank, K. D. (2006). Effects of artificial night lighting on moths. In C. Rich & T. Longcore (Eds.), Ecological consequences of artificial night lighting (pp. 305–344). Washington, DC: Island Press. Frank, K. D. (2006). Effects of artificial night lighting on moths. In C. Rich & T. Longcore (Eds.), Ecological consequences of artificial night lighting (pp. 305–344). Washington, DC: Island Press.
Zurück zum Zitat Garg, P., & Gupta, A. (2017). Optimized open shortest path first algorithm based on moth flame optimization. Indian Journal of Science and Technology, 9(48). Garg, P., & Gupta, A. (2017). Optimized open shortest path first algorithm based on moth flame optimization. Indian Journal of Science and Technology, 9(48).
Zurück zum Zitat Gope, S., Dawn, S., Goswami, A. K., & Tiwari, P. K. (2016, November 22–25). Moth Flame Optimization based optimal bidding strategy under transmission congestion in deregulated power market. In Region 10 Conference (TENCON). Marina Bay Sands, Singapore: IEEE. Gope, S., Dawn, S., Goswami, A. K., & Tiwari, P. K. (2016, November 22–25). Moth Flame Optimization based optimal bidding strategy under transmission congestion in deregulated power market. In Region 10 Conference (TENCON). Marina Bay Sands, Singapore: IEEE.
Zurück zum Zitat Jangir, N., Pandya, M. H., Trivedi, I. N., Bhesdadiya, R. H., Jangir, P., & Kumar, A. (2016, March 5–6). Moth-Flame Optimization algorithm for solving real challenging constrained engineering optimization problems. In Students’ Conference on Electrical, Electronics and Computer Science (SCEECS). Bhopal, India: IEEE. Jangir, N., Pandya, M. H., Trivedi, I. N., Bhesdadiya, R. H., Jangir, P., & Kumar, A. (2016, March 5–6). Moth-Flame Optimization algorithm for solving real challenging constrained engineering optimization problems. In Students’ Conference on Electrical, Electronics and Computer Science (SCEECS). Bhopal, India: IEEE.
Zurück zum Zitat Khalilpourazari, S., & Pasandideh, S. H. R. (2017). Multi-item EOQ model with nonlinear unit holding cost and partial backordering: Moth-flame optimization algorithm. Journal of Industrial and Production Engineering, 34(1), 42–51. Khalilpourazari, S., & Pasandideh, S. H. R. (2017). Multi-item EOQ model with nonlinear unit holding cost and partial backordering: Moth-flame optimization algorithm. Journal of Industrial and Production Engineering, 34(1), 42–51.
Zurück zum Zitat Lal, D. K., & Barisal, A. K. (2016, December 27–28). Load frequency control of AC microgrid interconnected thermal power system. In International Conference on Advanced Material Technologies (ICAMT). Andhra Pradesh, India. Lal, D. K., & Barisal, A. K. (2016, December 27–28). Load frequency control of AC microgrid interconnected thermal power system. In International Conference on Advanced Material Technologies (ICAMT). Andhra Pradesh, India.
Zurück zum Zitat Li, C., Li, S., & Liu, Y. (2016a). A least squares support vector machine model optimized by moth-flame optimization algorithm for annual power load forecasting. Applied Intelligence, 45(4), 1166–1178. Li, C., Li, S., & Liu, Y. (2016a). A least squares support vector machine model optimized by moth-flame optimization algorithm for annual power load forecasting. Applied Intelligence, 45(4), 1166–1178.
Zurück zum Zitat Li, Z., Zhou, Y., Zhang, S., & Song, J. (2016b). Lévy-flight moth-flame algorithm for function optimization and engineering design problems. Mathematical Problems in Engineering. doi:10.1155/2016/1423930. Li, Z., Zhou, Y., Zhang, S., & Song, J. (2016b). Lévy-flight moth-flame algorithm for function optimization and engineering design problems. Mathematical Problems in Engineering. doi:10.​1155/​2016/​1423930.
Zurück zum Zitat Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, 89, 228–249. Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, 89, 228–249.
Zurück zum Zitat Muangkote, N., Sunat, K., & Chiewchanwattana, S. (2016, July 13–15). Multilevel thresholding for satellite image segmentation with moth-flame based optimization. In The 13th International Joint Conference on Computer Science and Software Engineering. Khon Kaen, Thailand. Muangkote, N., Sunat, K., & Chiewchanwattana, S. (2016, July 13–15). Multilevel thresholding for satellite image segmentation with moth-flame based optimization. In The 13th International Joint Conference on Computer Science and Software Engineering. Khon Kaen, Thailand.
Zurück zum Zitat Nanda, S. J. (2016, September 21–24). Multi-objective Moth Flame Optimization. In Advances in Computing, Communications and Informatics (ICACCI). Jaipur, India: IEEE. Nanda, S. J. (2016, September 21–24). Multi-objective Moth Flame Optimization. In Advances in Computing, Communications and Informatics (ICACCI). Jaipur, India: IEEE.
Zurück zum Zitat Parmar, S. A., Pandya, M. H., Bhoye, M., Trivedi, I. N., Jangir, P., & Ladumor, D. (2016, April 7–8). Optimal active and Reactive Power dispatch problem solution using Moth-Flame Optimizer algorithm. In International Conference on Energy Efficient Technologies for Sustainability (ICEETS). Nagercoil, India: IEEE. Parmar, S. A., Pandya, M. H., Bhoye, M., Trivedi, I. N., Jangir, P., & Ladumor, D. (2016, April 7–8). Optimal active and Reactive Power dispatch problem solution using Moth-Flame Optimizer algorithm. In International Conference on Energy Efficient Technologies for Sustainability (ICEETS). Nagercoil, India: IEEE.
Zurück zum Zitat Raju, M., Saikia, L. C., & Saha, D. (2016, November 22–25). Automatic generation control in competitive market conditions with moth-flame optimization based cascade controller. In Region 10 Conference (TENCON). Marina Bay Sands, Singapore: IEEE. Raju, M., Saikia, L. C., & Saha, D. (2016, November 22–25). Automatic generation control in competitive market conditions with moth-flame optimization based cascade controller. In Region 10 Conference (TENCON). Marina Bay Sands, Singapore: IEEE.
Zurück zum Zitat Soliman, G. M. A., Khorshid, M. M. H., & Abou-El-Enien, T. H. M. (2016, July). Modified moth-flame optimization algorithms for terrorism prediction. International Journal of Application or Innovation in Engineering and Management, 5, 47–58. Soliman, G. M. A., Khorshid, M. M. H., & Abou-El-Enien, T. H. M. (2016, July). Modified moth-flame optimization algorithms for terrorism prediction. International Journal of Application or Innovation in Engineering and Management, 5, 47–58.
Zurück zum Zitat Trivedi, I. N., Kumar, A., Ranpariya, A. H., & Jangir, P. (2016, April 7–8). Economic Load Dispatch problem with ramp rate limits and prohibited operating zones solve using Levy Flight Moth-Flame optimizer. In International Conference on Energy Efficient Technologies for Sustainability (ICEETS). Nagercoil, India. Trivedi, I. N., Kumar, A., Ranpariya, A. H., & Jangir, P. (2016, April 7–8). Economic Load Dispatch problem with ramp rate limits and prohibited operating zones solve using Levy Flight Moth-Flame optimizer. In International Conference on Energy Efficient Technologies for Sustainability (ICEETS). Nagercoil, India.
Zurück zum Zitat Yamany, W., Fawzy, M., Tharwat, A., & Hassanien, A. E. (2015, December 29–30). Moth-flame optimization for training multi-layer perceptrons. In 11th International Computer Engineering Conference (ICENCO). Giza, Egypt: IEEE. Yamany, W., Fawzy, M., Tharwat, A., & Hassanien, A. E. (2015, December 29–30). Moth-flame optimization for training multi-layer perceptrons. In 11th International Computer Engineering Conference (ICENCO). Giza, Egypt: IEEE.
Zurück zum Zitat Zawbaa, H. M., Emary, E., Parv, B., & Sharawi, M. (2016, July 24–29). Feature selection approach based on moth-flame optimization algorithm. In Evolutionary Computation (CEC). IEEE. Zawbaa, H. M., Emary, E., Parv, B., & Sharawi, M. (2016, July 24–29). Feature selection approach based on moth-flame optimization algorithm. In Evolutionary Computation (CEC). IEEE.
Metadaten
Titel
Moth-Flame Optimization (MFO) Algorithm
verfasst von
Mahdi Bahrami
Omid Bozorg-Haddad
Xuefeng Chu
Copyright-Jahr
2018
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-10-5221-7_13

Premium Partner