Solving continuous min-max problems by an iterative entropic regularization method

R. L. Sheu, J. Y. Lin

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)


We propose a method of outer approximations, with each approximate problem smoothed using entropic regularization, to solve continuous min-max problems. By using a well-known uniform error estimate for entropic regularization, convergence of the overall method is shown while allowing each smoothed problem to be solved inexactly. In the case of convex objective function and linear constraints, an interior-point algorithm is proposed to solve the smoothed problem inexactly. Numerical examples are presented to illustrate the behavior of the proposed method.

Original languageEnglish
Pages (from-to)597-612
Number of pages16
JournalJournal of Optimization Theory and Applications
Issue number3
Publication statusPublished - 2004 Jun

All Science Journal Classification (ASJC) codes

  • Control and Optimization
  • Management Science and Operations Research
  • Applied Mathematics


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