Table of Contents
International Journal of Combinatorics
Volume 2011, Article ID 523806, 23 pages
http://dx.doi.org/10.1155/2011/523806
Research Article

Application of the Firefly Algorithm for Solving the Economic Emissions Load Dispatch Problem

Department of Informatics, University of Piraeus, 80 Karaoli and Dimitriou Street, 18534 Piraeus, Greece

Received 30 August 2010; Accepted 14 November 2010

Academic Editor: Hajo Broersma

Copyright © 2011 Theofanis Apostolopoulos and Aristidis Vlachos. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. X. S. Yang, Nature-Inspired Meta-Heuristic Algorithms, Luniver Press, Beckington, UK, 2008.
  2. S. Lukasik and S. Zak, “Firefly algorithm for con-tinuous constrained optimization tasks,” in Proceedings of the International Conference on Computer and Computational Intelligence (ICCCI '09), N. T. Nguyen, R. Kowalczyk, and S.-M. Chen, Eds., vol. 5796 of LNAI, pp. 97–106, Springer, Wroclaw, Poland, October 2009.
  3. X. S. Yang, “Firefly algorithms for multimodal optimization,” in Proceedings of the Stochastic Algorithms: Foundations and Applications (SAGA '09), vol. 5792 of Lecture Notes in Computing Sciences, pp. 178–178, Springer, Sapporo, Japan, October 2009.
  4. X. S. Yang, “Firefly algorithm, Levy flights and global optimization,” in Research and Development in Intelligent Systems XXVI, pp. 209–218, Springer, London, UK, 2010. View at Google Scholar
  5. K. S. Kumar, V. Tamilselvan, N. Murali, R. Rajaram, N. S. Sundaram, and T. Jayabarathi, “Economic load dispatch with emission constraints using various PSO algorithms,” WSEAS Transactions on Power Systems, vol. 3, no. 9, pp. 598–607, 2008. View at Google Scholar
  6. M. Basu, “A simulated annealing-based goal-attainment method for economic emission load dispatch of fixed head hydrothermal power systems,” International Journal of Electrical Power and Energy Systems, vol. 27, no. 2, pp. 147–153, 2005. View at Publisher · View at Google Scholar
  7. On-line Matlab Tutorials, The MathWorksTM Support web-page, Documentation of Optimization Toolbox, Topics: Goal Attainment Method, Sequential Quadratic Pro-gramming & Multi-objective Optimization http://www.mathworks.com.au/help/toolbox/optim/.
  8. P. C. Chen and C. M. Huang, “Biobjective power dispatch using goal-attainment method and adaptive polynomial networks,” IEEE Transactions on Energy Conversion, vol. 19, no. 4, pp. 741–747, 2004. View at Publisher · View at Google Scholar
  9. T. Bouktir, R. Labdani, and L. Slimani, “Economic power dispatch of power system with pollution control using multi-objective particle swarm optimization,” Journal of Pure & Applied Sciences, vol. 4, no. 2, pp. 57–77, 2007. View at Google Scholar
  10. W. F. Abd El-Wahed, A. A. Mousa, and M. A. Elsisy, “Solving economic emissions load dispatch problem by using hybrid ACO-MSM approach,” The Online Journal on Power and Energy Engineering, vol. 1, no. 1, 2009. View at Google Scholar
  11. E. Zitzler, M. Laumanns, and S. Bleuler, “A Tuto-rial on Evolutionary Multi-objective Optimization,” Swiss Federal Institute of Technology (ETH) Zurich, Computer Engineering and Networks Laboratory (TIK), Zurich, Switzerland.
  12. J. Cooper, A MATLAB® Companion for Multivariable Calculus, A Harcourt Science and Technology Company/Academic Press, 2001.
  13. L. Xie, S. Wang, and Z. Wu, “Study on economic, rapid and environmental power dispatch based on fuzzy multi-objective optimization,” Modern Applied Science, vol. 3, no. 6, pp. 38–44, 2009. View at Google Scholar
  14. S. S. RAO, Engineering Optimization Theory and Practice, John Wiley & Sons, New York, NY, USA, 4th edition, 2009.
  15. J. S. Alsumait and J. K. Sykulski, “Solving economic dispatch problem using hybrid GA-PS-SQP method,” in Proceedings of the International Conference on Computer as a Tool (EUROCON '09), pp. 351–356, Saint Petersburg, Russia, May 2009.
  16. M. Sudhakaran, S. M. R. Slochanal, R. Sreeram, and N. Chandrasekhar, “Application of refined genetic algorithm to combined economic and emission dispatch,” Journal of the Institution of Engineers, vol. 85, no. 2, pp. 115–119, 2004. View at Google Scholar
  17. R. Gonçalves, C. Almeida, J. Kuk, and M. Delgado, “Solving economic load dispatch problem by natural computing intelligent systems,” in Proceedings of the 15th International Conference on Intelligent System Applications to Power Systems (ISAP '09), Curitiba, Brazil, November 2009. View at Publisher · View at Google Scholar
  18. Y. P. Verma and A. Kumar, “Economic load dispatch solutions using new particle swarm intelligence,” in Proceedings of the 5th National Power Systems Conference (NPSC '08), pp. 220–225, IIT, Bombay, India, December 2008.
  19. C. Palanichamy and N. S. Babu, “Analytical solution for combined economic and emissions dispatch,” Electric Power Systems Research, vol. 78, no. 7, pp. 1129–1137, 2008. View at Publisher · View at Google Scholar
  20. X. S. Yang, “Firefly algorithm, stochastic test functions and design optimisation,” International Journal of Bio-Inspired Computation, vol. 2, no. 2, pp. 78–84, 2010. View at Google Scholar