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Mathematical Problems in Engineering
Volume 2015, Article ID 541782, 8 pages
http://dx.doi.org/10.1155/2015/541782
Research Article

A Nondominated Genetic Algorithm Procedure for Multiobjective Discrete Network Design under Demand Uncertainty

1Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China
2China Academy of Urban Planning and Design, Beijing 100044, China

Received 9 December 2014; Accepted 12 January 2015

Academic Editor: Wei (David) Fan

Copyright © 2015 Bian Changzhi. 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. H. Yang and M. G. H. Bell, “Models and algorithms for road network design: a review and some new developments,” Transport Reviews, vol. 18, no. 3, pp. 257–278, 1998. View at Publisher · View at Google Scholar · View at Scopus
  2. L. J. Leblanc, “An algorithm for the discrete network design problem,” Transportation Science, vol. 9, no. 3, pp. 183–199, 1975. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Chen and A. S. Alfa, “A network design algorithm using a stochastic incremental traffic assignment approach,” Transportation Science, vol. 25, no. 3, pp. 215–224, 1991. View at Publisher · View at Google Scholar · View at Scopus
  4. Z. Y. Gao, J. J. Wu, and H. J. Sun, “Solution algorithm for the bi-level discrete network design problem,” Transportation Research Part B: Methodological, vol. 39, no. 6, pp. 479–495, 2005. View at Publisher · View at Google Scholar · View at Scopus
  5. H. Farvaresh and M. M. Sepehri, “A branch and bound algorithm for bi-level discrete network design problem,” Networks and Spatial Economics, vol. 13, no. 1, pp. 67–106, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  6. S. Wang, Q. Meng, and H. Yang, “Global optimization methods for the discrete network design problem,” Transportation Research Part B: Methodological, vol. 50, pp. 42–60, 2013. View at Publisher · View at Google Scholar · View at Scopus
  7. Y. Sun and M. A. Turnquist, “Investment in transportation network capacity under uncertainty simulated annealing approach,” Transportation Research Record, vol. 2039, pp. 67–74, 2007. View at Publisher · View at Google Scholar · View at Scopus
  8. S. V. Ukkusuri, T. V. Mathew, and S. T. Waller, “Robust transportation network design under demand uncertainty,” Computer-Aided Civil and Infrastructure Engineering, vol. 22, no. 1, pp. 6–18, 2007. View at Publisher · View at Google Scholar · View at Scopus
  9. B. D. Chung, T. Yao, C. Xie, and A. Thorsen, “Robust optimization model for a dynamic network design problem under demand uncertainty,” Networks and Spatial Economics, vol. 11, no. 2, pp. 371–389, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  10. A. Chen, K. Subprasom, and Z. Ji, “Mean-variance model for the build-operate-transfer scheme under demand uncertainty,” Transportation Research Record, no. 1857, pp. 93–101, 2003. View at Google Scholar · View at Scopus
  11. D.-Y. Lin and C. Xie, “The Pareto-optimal solution set of the equilibrium network design problem with multiple commensurate objectives,” Networks and Spatial Economics, vol. 11, no. 4, pp. 727–751, 2011. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  12. M. Yang, B. Su, Z. Sun, and Y. Xu, “Model and algorithm of multi-objective discrete transportation network design under stochastic demand among OD pairs,” Journal of Southwest Jiaotong University, vol. 49, no. 1, pp. 119–125, 2014. View at Google Scholar · View at Scopus
  13. J. H. Holland, Adapation in Natural and Artificial Systems, The University of Michigan Press, Ann Arbor, Mich, USA, 1975. View at MathSciNet
  14. D. E. Goldberg, Genetic Algorithm in Search, Optimization and Machine Learning, Addison-Wesley, Boston, Mass, USA, 1989.
  15. K. Deb, Multi-Objective Optimization Using Evolutionary Algorithms, John Wiley & Sons, Chichester, UK, 2002.
  16. Y. Yin, “Genetic-algorithms-based approach for bilevel programming models,” Journal of Transportation Engineering, vol. 126, no. 2, pp. 115–120, 2000. View at Publisher · View at Google Scholar · View at Scopus
  17. K. Jeon, J. S. Lee, S. Ukkusuri, and S. T. Waller, “Selectorecombinative genetic algorithm to relax computational complexity of discrete network design problem,” Transportation Research Record, no. 1964, pp. 91–103, 2006. View at Google Scholar · View at Scopus
  18. A. Chen, K. Subprasom, and Z. Ji, “A simulation-based multi-objective genetic algorithm (SMOGA) procedure for BOT network design problem,” Optimization and Engineering, vol. 7, no. 3, pp. 225–247, 2006. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  19. 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
  20. Y. Sheffi, Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming Methods, Prentice Hall, Englewood Cliffs, NJ, USA, 1985.
  21. S. Nguyen and C. Dupuis, “An efficient method for computing traffic equilibria in networks with asymmetric transportation costs,” Transportation Science, vol. 18, no. 2, pp. 185–202, 1984. View at Publisher · View at Google Scholar · View at Scopus
  22. B. J. Kim, W. Kim, and B. H. Song, “Sequencing and scheduling highway network expansion using a discrete network design model,” Annals of Regional Science, vol. 42, no. 3, pp. 621–642, 2008. View at Publisher · View at Google Scholar · View at Scopus
  23. H. M. Markowitz, “Portfolio selection,” The Journal of Finance, vol. 7, no. 1, pp. 77–91, 1952. View at Publisher · View at Google Scholar