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Computational Optimization and Applications

, Volume 38, Issue 3, pp 299–303 | Cite as

A local relaxation approach for the siting of electrical substation

  • Walter Murray
  • Uday V. Shanbhag
COAP 2006 Best Paper Award

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References

  1. 1.
    Gill, P.E., Murray, W., Saunders, M.A.: User’s guide for sqopt 5.3: a Fortan package for large-scale linear and quadratic programming. Technical report, Systems Optimization Laboratory, Department of Operations Research, Stanford University (1997) Google Scholar
  2. 2.
    Gill, P.E., Murray, W., Saunders, M.A.: SNOPT: an SQP algorithm for large-scale constrained optimization. SIAM Rev. 47, 99–131 (2005) (electronic) MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Grossmann, I., Viswanathan, J., Vecchietti, A., Raman, R., Kalvelagen, E.: Gams/dicopt: a discrete continuous optimization package Google Scholar
  4. 4.
    Murray, W., Shanbhag, U.V.: A local relaxation method for nonlinear facility location problems. In: Multiscale Optimization Methods and Applications. Nonconvex Optimization and Applications, vol. 82, pp. 173–204. Springer, New York (2006) CrossRefGoogle Scholar
  5. 5.
    Ng, K.-M.: A continuation approach to solving continuous problems with discrete variables. Ph.D. thesis, Stanford University, Stanford, CA (June 2002) Google Scholar
  6. 6.
    Sahinidis, N.: Baron: a general purpose global optimization software package. J. Glob. Optim. 8, 201–205 (1996) MATHCrossRefMathSciNetGoogle Scholar
  7. 7.
    Sahinidis, N.V., Tawarmalani, M.: BARON 7.2: Global Optimization of Mixed-Integer Nonlinear Programs. User’s Manual (2004) Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  1. 1.Department of Management Science and EngineeringStanford UniversityStanfordUSA
  2. 2.Department of Industrial and Enterprise Systems EngineeringUniversity of Illinois at Urbana-ChampaignUrbanaUSA

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