Applied Mathematics and Mechanics (English Edition) ›› 2012, Vol. 33 ›› Issue (2): 253-270.doi: https://doi.org/10.1007/s10483-012-1548-6

• Articles • 上一篇    

New exact penalty function for solving constrained finite min-max problems

马骋1 李讯1 姚家辉1 张连生2   

  1. 1. Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China;
    2. Department of Mathematics, College of Sciences, Shanghai University, Shanghai 200444, P. R. China
  • 收稿日期:2011-03-21 修回日期:2011-11-23 出版日期:2012-01-11 发布日期:2012-02-01

New exact penalty function for solving constrained finite min-max problems

 MA Cheng1, LI Xun1, Ka-Fai CEDRICYIU1, ZHANG Lian-Sheng2   

  1. 1. Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong, P. R. China;
    2. Department of Mathematics, College of Sciences, Shanghai University, Shanghai 200444, P. R. China
  • Received:2011-03-21 Revised:2011-11-23 Online:2012-01-11 Published:2012-02-01

摘要: This paper introduces a new exact and smooth penalty function to tackle constrained min-max problems. By using this new penalty function and adding just one extra variable, a constrained min-max problem is transformed into an unconstrained optimization one. It is proved that, under certain reasonable assumptions and when the penalty parameter is sufficiently large, the minimizer of this unconstrained optimization problem is equivalent to the minimizer of the original constrained one. Numerical results demonstrate that this penalty function method is an effective and promising approach for solving constrained finite min-max problems.

Abstract: This paper introduces a new exact and smooth penalty function to tackle constrained min-max problems. By using this new penalty function and adding just one extra variable, a constrained min-max problem is transformed into an unconstrained optimization one. It is proved that, under certain reasonable assumptions and when the penalty parameter is sufficiently large, the minimizer of this unconstrained optimization problem is equivalent to the minimizer of the original constrained one. Numerical results demonstrate that this penalty function method is an effective and promising approach for solving constrained finite min-max problems.

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