A hybrid algorithm for linearly constrained minimax problems

Fusheng Wang ()

Annals of Operations Research, 2013, vol. 206, issue 1, 525 pages

Abstract: Many real life problems can be stated as a minimax problem, such as economics, finance, management, engineering and other fields, which demonstrate the importance of having reliable methods to tackle minimax problems. In this paper, an algorithm for linearly constrained minimax problems is presented in which we combine the trust-region methods with the line-search methods and curve-search methods. By means of this hybrid technique, it avoids possibly solving the trust-region subproblems many times, and make better use of the advantages of different methods. Under weaker conditions, the global and superlinear convergence are achieved. Numerical experiments show that the new algorithm is robust and efficient. Copyright Springer Science+Business Media New York 2013

Keywords: Nonlinear programming; Linearly constrained minimax problems; Trust-region methods; Hybrid technique; Superlinear convergence (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10479-012-1274-3

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