Table of Contents Author Guidelines Submit a Manuscript
Advances in Civil Engineering
Volume 2011, Article ID 932871, 24 pages
http://dx.doi.org/10.1155/2011/932871
Research Article

Multiobjective Design Optimization of Grillage Systems according to LRFD-AISC

High Vocational School of Kadirli, Osmaniye Korkut Ata University, 80000 Osmaniye, Turkey

Received 9 November 2010; Revised 18 May 2011; Accepted 29 May 2011

Academic Editor: Manolis Papadrakakis

Copyright © 2011 Tugrul Talaslioglu. 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. J. D. Schaffer, Multiple objective optimization with vector evaluated genetic algorithms, Ph.D. thesis, Vanderbilt University, 1984.
  2. I. Das and J. E. Dennis, “A closer look at drawbacks of minimizing weighted sums of objectives for pareto set generation in multicriteria optimization problems,” Structural Optimization, vol. 14, no. 1, pp. 63–69, 1997. View at Google Scholar · View at Scopus
  3. A. Hertz, B. Jaumard, C. Ribeiro, and W. F. Filho, “A multi-criteria tabu search approach to cell formation problems in group technology with multiple objectives,” RAIRO—Operations Research, vol. 28, no. 3, pp. 303–328, 1994. View at Google Scholar
  4. D. E. Goldberg, Genetic Algorithms in Search. Optimization and Machine Learning, Addison-Wesley Publishing, Massachusetts, Mass, USA, 1989.
  5. N. Srinivas and K. Deb, “Multiobjective optimization using nondominated sorting in genetic algorithms,” Evolutionary Computation, vol. 2, no. 3, pp. 221–248, 1994. View at Google Scholar
  6. J. N. Horn, A. L. Nafpliotis, and D. E. Goldberg, “A niched Pareto genetic algorithm for multiobjective optimization,” in Proceedings of the First IEEE Conference on Evolutionary Computation, IEEE World Congress on Computational Intelligence, pp. 82–87, IEEE Service Center, Piscataway, NJ, USA, Jun 1994.
  7. C. M. Fonseca and F. J. Fleming, “Genetic algorithms for multiobjective optimization: formulation, discussion and generalization,” in Proceedings of the Fifth International Conference on Genetic Algorithms, S. Forrest, Ed., pp. 416–423, Morgan Kauffman, San Mateo, Calif, USA, June 1993.
  8. M. Tanaka and T. Tanino, “Global optimization by the genetic algorithm in a multiobjective decision support system,” in Proceedings of the 10th International Conference on Multiple Criteria Decision Making, pp. 261–270, Taipei, China, July 1992.
  9. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, Chichester, UK, 2001.
  10. E. Zitzler and L. Thiele, “Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach,” IEEE Transactions on Evolutionary Computation, vol. 3, no. 4, pp. 257–271, 1999. View at Google Scholar · View at Scopus
  11. J. D. Knowles and D. W. Corne, “Approximating the nondominated front using the Pareto archived evolution strategy,” Evolutionary Computation, vol. 8, no. 2, pp. 149–172, 2000. View at Google Scholar · View at Scopus
  12. K. Deb and T. Goel, “Controlled elitist non-dominated sorting genetic algorithms for better convergence,” Lecture Notes in Computer Science, vol. 1993, pp. 67–81, 2001. View at Google Scholar
  13. S. S. Rao, V. B. Venkayya, and N. S. Khot, “Optimization of actively controlled structures using goal programming techniques,” International Journal for Numerical Methods in Engineering, vol. 26, no. 1, pp. 183–197, 1988. View at Google Scholar · View at Scopus
  14. J. P. Ignizio, Goal Programming and Extensions, Heath, Boston, Mass, USA, 1976.
  15. S. S. Rao and T. I. Freiheit, “Modified game theory approach to multiobjective optimization,” Journal of Mechanisms, Transmissions, and Automation in Design, vol. 113, no. 3, pp. 286–291, 1991. View at Google Scholar · View at Scopus
  16. M. Sunar and R. Kahraman, “A comparative study of multiobjective optimization methods in structural design,” Turkish Journal of Engineering and Environmental Sciences, vol. 25, no. 2, pp. 69–78, 2001. View at Google Scholar · View at Scopus
  17. J. Koski, “Defectiveness of weighting method in multicriterion optimization of structures,” Communications in Numerical Methods in Engineering, vol. 1, no. 6, pp. 333–337, 1985. View at Google Scholar · View at Scopus
  18. I. Das and J. E. Dennis, “A closer look at drawbacks of minimizing weighted sums of objectives for Pareto set generation in multicriteria optimization problems,” Structural Optimization, vol. 14, no. 1, pp. 63–69, 1997. View at Google Scholar · View at Scopus
  19. A. Messac and C. A. Mattson, “Generating well-distributed sets of Pareto points for engineering design using physical programming,” Optimization and Engineering, vol. 3, no. 4, pp. 431–450, 2002. View at Google Scholar
  20. I. Y. Kim and O. L. Weck, “Adaptive weighted-sum method for bi-objective optimization: Pareto front generation,” Structural and Multidisciplinary Optimization, vol. 29, no. 2, pp. 149–158, 2005. View at Publisher · View at Google Scholar · View at Scopus
  21. A. Molina-Cristobal, L. A. Griffin, P. J. Fleming, and D. H. Owens, “Multiobjective controller design: optimising controller structure with genetic algorithms,” in Proceedings of the 16th IFAC World Congress on Automatic Control, Prague, Czech Republic, July 2005.
  22. C. A. C. Coello and N. C. Cortes, “Solving multiobjective optimization problems using an artificial immune system,” Genetic Programming and Evolvable Machines, vol. 6, no. 2, pp. 163–190, 2005. View at Publisher · View at Google Scholar · View at Scopus
  23. M. Guntsch, Ant algorithms in stochastic and multi-criteria environments, Ph.D. thesis, Department of Economics and Business Engineering, University of Karlsruhe, Germany, 2004.
  24. C. A. Coello and P. G. Toscano, “Multiobjective optimization using a micro-genetic algorithm,” in Proceedings of the Genetic And Evolutionary Computation Conference, (GECCO '01), L. Spector et al., Ed., pp. 174–282, Morgan Kaufmann, San Francisco, Calif, USA, August 2001.
  25. R. M. Janga and K. D. Nagesh, “An efficient multi-objective optimization algorithm based on swarm intelligence for engineering design,” Engineering Optimization, vol. 39, no. 1, pp. 49–68, 2007. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  26. N. Keerativuttitumrong, N. Chaiyaratana, and V. Varavithya, “Multi-objective co-operative co-evolutionary genetic algorithm,” Lecture Notes in Computer Science, vol. 2439, pp. 288–297, 2002. View at Google Scholar
  27. C. M. Fonseca and P. J. Fleming, “Genetic algorithms for multiobjective optimization: formulation, discussion and generalization,” in Proceedings of the 5th International Conference on Genetic Algorithms, pp. 416–423, Urbana-Champaign, Ill, USA, June 1993.
  28. J. Horn and N. Nafpliotis, “Multiobjective optimization using the niched Pareto genetic algorithm,” IlliGAL Report 93005, Illinois Genetic Algorithms Laboratory, University of Illinois, Urbana-Champaign, Ill, USA, 1993. View at Google Scholar
  29. A. R. Khorsand and M. R. Akbarzadeh, “Multi-objective meta level soft computing-based evolutionary structural design,” Journal of the Franklin Institute, vol. 344, no. 5, pp. 595–612, 2007. View at Publisher · View at Google Scholar · View at Scopus
  30. M. P. Saka, A. Daloglu, and F. Malhas, “Optimum spacing design of grillage systems using a genetic algorithm,” Advances in Engineering Software, vol. 31, no. 11, pp. 863–873, 2000. View at Publisher · View at Google Scholar · View at Scopus
  31. F. Erdal and M. P. Saka, “Effect of beam spacing in the harmony search based optimum design of grillages,” Asian Journal of Civil Engineering, vol. 9, no. 3, pp. 215–228, 2008. View at Google Scholar
  32. M. P. Saka and F. Erdal, “Harmony search based algorithm for the optimum design of grillage systems to LRFD-AISC,” Structural and Multidisciplinary Optimization, vol. 38, no. 1, pp. 25–41, 2009. View at Publisher · View at Google Scholar · View at Scopus
  33. J. K. Nelson and J. C. McCormac, Structural Analysis 3E WSE: Using Classical and Matrix Methods, John Wiley & Sons, New York, NY, USA, 2003.
  34. http://jmetal.sourceforge.net/.
  35. K. Deb, S. Agrawal, A. Pratab, and T. Meyarivan, “A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization:NSGA-II,” in Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, (PPSN '00), M. Schoenauer, K. Deb, G. Rudolph et al., Eds., pp. 849–858, Paris, France, September 2000.
  36. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, “A fast and elitist multiobjective genetic algorithm: NSGA-II,” IEEE Transactions on Evolutionary Computation, vol. 6, no. 2, pp. 182–197, 2002. View at Publisher · View at Google Scholar · View at Scopus
  37. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, New York, NY, USA, 2001.
  38. D. W. Corne, J. D. Knowles, and M. J. Oates, “The Pareto envelope-based selection algorithm for multiobjective optimization,” in Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, (PPSN '00), M. Schoenauer, K. Deb, G. Rudolph et al., Eds., pp. 839–848, Paris, France, September 2000.
  39. D. W. Corne, N. R. Jerram, J. D. Knowles, and M. J. Oates, “PESA-II: regionbased selection in evolutionary multiobjective optimization,” in Proceedings of the the Genetic and Evolutionary Computation Conference, (GECCO '01), L. Spector, E. D. Goodman, A. Wu et al., Eds., pp. 283–290, San Francisco, Calif, USA, July 2001.
  40. K. Deb, M. Mohan, and S. Mishra, “Towards a quick computation of well-spread pareto-optimal solutions,” in Proceedings of the Second International Conference on Evolutionary Multi-Criterion Optimization, (EMO '03), C. M. Fonseca, P. J. Fleming, E. Zitzler, K. Deb, and L. Thiele, Eds., pp. 222–236, Faro, Portugal, April, 2003.
  41. A. J. Nebro, F. Luna, E. Alba, B. Dorronsoro, J. J. Durillo, and A. Beham, “AbYSS: adapting scatter search to multiobjective optimization,” IEEE Transactions on Evolutionary Computation, vol. 12, no. 4, pp. 439–457, 2008. View at Publisher · View at Google Scholar · View at Scopus
  42. The MathWorks, “Statistical toolbox User's Guide,” 2008. View at Google Scholar