Discrete Optimization

  • Urmila Diwekar
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 22)

Keywords

Genetic Algorithm Simulated Annealing Mixed Integer Linear Programming Master Problem Discrete Optimization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Bibliography

  1. •.
    Ahuja R. K. and J. B. Orlin (1997), Developing fitter genetic algorithms,INFORMS Journal of Computing,9(3), 251.CrossRefGoogle Scholar
  2. •.
    Beale E. M. (1977),Integer Programming: The State of the Art in Numerical Analysis, Academic Press, London.Google Scholar
  3. •.
    Biegler L., I. E. Grossmann, and A. W. Westerberg (1997),Systematic Methods of Chemical Process Design, Prentice-Hall, Upper Saddle River, NJ.Google Scholar
  4. •.
    Chauduri P., U. M. Diwekar, and J. F. Logsdon, An automated approach to optimal heat exchanger design (1997),Ind. Eng. Chem. Res.,36, 2685.Google Scholar
  5. •.
    Chiba, T., S. Okado, and I. Fujii (1996), Optimum support arrangement of piping systems using genetic algorithm,Journal of Pressure Vessel Technology,118, 507.CrossRefGoogle Scholar
  6. •.
    Collins N. E., R. W. Eglese, and B. L. Golden (1988), Simulated annealing—An annotated biography,American Journal of Mathematical and Management Science,8(3), 209.MATHMathSciNetGoogle Scholar
  7. •.
    Diwekar U. M., I. E. Grossmann, and E. S. Rubin (1991), An MINLP process synthesizer for a sequential modular simulator,Industrial and Engineering Chemistry Research,31, 313.CrossRefGoogle Scholar
  8. •.
    Dunn, S.A. (1997), Modified genetic algorithm for the identification of aircraft structures,Journal of Aircraft,34, 251.CrossRefGoogle Scholar
  9. •.
    Glover F. (1986), Future paths for integer programming and links to artificial intelligence,Computers and Operations Research,5, 533.CrossRefMathSciNetGoogle Scholar
  10. •.
    Goldberg D.E. (1989),Genetic Algorithms in Search, Optimization and Machine Learning, Addison-Wesley, Reading MA.MATHGoogle Scholar
  11. •.
    Guarnieri F. and M. Mezei (1996), Simulated annealing of chemical potential: A general procedure for locating bound waters. Application to the study of the differential hydration propensities of the major and minor grooves of DNA,Journal of the American Chemical Society,118, 8493.CrossRefGoogle Scholar
  12. •.
    Hendry J. E. and R. R. Hughes (1972), Generating separation flowsheets,Chemical Engineering Progress,68, 69.Google Scholar
  13. •.
    Holland J. H. (1975),Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor.Google Scholar
  14. •.
    Holland J. H. (1992), Genetic algorithms,Scientific American, July, 66.Google Scholar
  15. •.
    Huang M. D., F. Romeo, and A. L. Sangiovanni-Vincetelli (1986), An efficient general cooling schedule for simulated annealing,Proceedings of IEEE Conference on Computer Design, 381.Google Scholar
  16. •.
    Joseph D. and W. Kinsner (1997) Design of a parallel genetic algorithm for the Internet, IEEE WESCANEX 97 Communications, Power and Computing. Conference Proceedings, 333.Google Scholar
  17. •.
    Kershenbaum A. (1997), When genetic algorithms work best,INFORMS Journal of Computing,9(3), 254.CrossRefGoogle Scholar
  18. •.
    Kirkpatrick S., C. Gelatt, and M. Vecchi (1983), Optimization by simulated annealing,Science,220(4598), 670.CrossRefMathSciNetGoogle Scholar
  19. •.
    Lettau M. (1997), Explaining the facts with adaptive agents: The case of mutual fund flows,Journal of Economic Dynamics and Control,21(7), 1117.CrossRefMATHGoogle Scholar
  20. •.
    Levine D. (1997), Genetic algorithms: A practitioner’s view,INFORMS Journal of Computing,9(3), 256.CrossRefGoogle Scholar
  21. •.
    Narayan V., U. M. Diwekar, and M. Hoza (1996), Synthesizing optimal waste blends,Industrial and Engineering Chemistry Research,35, 3519.CrossRefGoogle Scholar
  22. •.
    Painton L. and U. M. Diwekar (1994), Synthesizing optimal design configurations for a Brayton cycle power plant,Computers & Chemical Engineering,18, 369.CrossRefGoogle Scholar
  23. •.
    Price T. C. (1997), Using co-evolutionary programming to simulate strategic behavior in markets,Journal of Evolutionary Economics,7(3), 219.CrossRefGoogle Scholar
  24. •.
    Reeves C. R. (1997), Genetic algorithms: No panacea, but a valuable tool for the operations researcher,INFORMS Journal of Computing,9(3), 263.CrossRefGoogle Scholar
  25. •.
    Ross P. (1997), What are genetic algorithms good at?,INFORMS Journal of Computing,9(3), 260.CrossRefGoogle Scholar
  26. •.
    Shapiro B. A. and J. C. Wu (1997) Predicting RNA H-type pseudoknots with the massively parallel genetic algorithm,Comput. Appl. Biosci.,13(4), 459.Google Scholar
  27. •.
    Subramanian D. K. and K. Subramanian (1998), Query optimization in multidatabase systems,Distributed and Parallel Databases,6(2), 183.CrossRefGoogle Scholar
  28. •.
    Taha H. A. (1997),Operations Research: An Introduction, Sixth Edition, Prentice-Hall, Upper Saddle River, NJ.MATHGoogle Scholar
  29. •.
    Tayal M. and U. Diwekar (2001), Novel sampling approach to optimal molecular design under uncertainty: A polymer design case study,AIChE Journal,47(3), 609.CrossRefGoogle Scholar
  30. •.
    VanLaarhoven P. J. M. and E. H. Aarts (1987),Simulated Annealing Theory and Applications, D. Reidel, Holland.Google Scholar
  31. •.
    Vazquez-Espi, C. and Vazquez, M. (1997), Sizing, shape and topology design optimization of trusses using genetic algorithm.Journal of Structural Engineering,123, 375-7.CrossRefGoogle Scholar
  32. •.
    Winston W. L. (1991),Operations Research: Applications and Algorithms, Second Edition, PWS-KENT, Boston.MATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Urmila Diwekar
    • 1
  1. 1.University of Illinois at ChicagoUSA

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