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A Lagrange penalty reformulation method for constrained optimization

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Abstract

In this paper a constrained optimization problem is transformed into an equivalent one in terms of an auxiliary penalty function. A Lagrange function method is then applied to this transformed problem. Zero duality gap and exact penalty results are obtained without any coercivity assumption on either the objective function or constraint functions.

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References

  1. Burachik R.S., Rubinov A.M. (2005). On the absence of duality gap for Lagrange-type functions. J. Ind. Manage. Optim. 1(1):33–38

    MATH  MathSciNet  Google Scholar 

  2. Huang X.X., Yang X.Q. (2003). A unified augmented Lagrangian approach to duality and exact penalization. Math. Oper. Res. 28(3):533–552

    Article  MATH  MathSciNet  Google Scholar 

  3. Luenberger D.G. (1984). Linear and Nonlinear Programming. Addison-Wesley, Reading

    MATH  Google Scholar 

  4. Rockafellar R.T., Wets R.J.-B. (1998). Variational Analysis. Springer, Berlin Heidelberg New York

    MATH  Google Scholar 

  5. Rubinov A.M., Huang X.X., Yang X.Q. (2002). The zero duality gap property and lower semicontinuity of the perturbation function. Math. Oper. Res. 27(4):775–791

    Article  MATH  MathSciNet  Google Scholar 

  6. Rubinov A.M., Yang X.Q. (2003). Lagrange-Type Functions in Constrained Non-Convex Optimization. Kluwer, Dordrecht

    MATH  Google Scholar 

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Authors and Affiliations

  1. School of Information Technology and Mathematical Sciences, University of Ballarat, Ballarat, VIC, Australia

    A. M. Rubinov

  2. Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China

    X. Q. Yang

  3. Department of Mathematics, Suzhou University, Suzhou, Jiangsu, 215006, China

    Y. Y. Zhou

Authors
  1. A. M. Rubinov
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  2. X. Q. Yang
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  3. Y. Y. Zhou
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Corresponding author

Correspondence to A. M. Rubinov.

Additional information

The work of the authors was supported by the Australian Research Council (grant DP0343998), the Research Grants Council of Hong Kong (PolyU 5145/02E) and NNSF (10571174) of China, respectively.

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Rubinov, A.M., Yang, X.Q. & Zhou, Y.Y. A Lagrange penalty reformulation method for constrained optimization. Optimization Letters 1, 145–154 (2007). https://doi.org/10.1007/s11590-006-0010-9

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  • DOI: https://doi.org/10.1007/s11590-006-0010-9

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