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dc.contributor.authorRoyset, J.O.
dc.contributor.authorPee, E.Y.
dc.date2012
dc.date.accessioned2014-01-09T22:24:09Z
dc.date.available2014-01-09T22:24:09Z
dc.date.issued2012
dc.identifier.citationJ.O. Royset and E.Y. Pee, 2012, "Rate of Convergence Analysis of Discretization and Smoothing Algorithms for Semi-Infinite Minimax Problems," Journal of Optimization Theory and Applications, Vol. 155, No. 3, pp. 855-882.
dc.identifier.citationRoyset, Johannes O., and E. Y. Pee. "Rate of convergence analysis of discretization and smoothing algorithms for semiinfinite minimax problems." Journal of Optimization Theory and Applications 155.3 (2012): 855-882.
dc.identifier.urihttp://hdl.handle.net/10945/38226
dc.description.abstractDiscretization algorithms for semi-infinite minimax problems replace the original problem, containing an infinite number of functions, by an approximation involving a finite number, and then solve the resulting approximate problem. The approximation gives rise to a discretization error, and suboptimal solution of the approximate problem gives rise to an optimization error. Accounting for both discretization and optimization errors, we determine the rate of convergence of discretization algorithms, as a computing budget tends to infinity. We find that the rate of convergence depends on the class of optimization algorithms used to solve the approximate problem as well as the policy for selecting discretization level and number of optimization iterations. We construct optimal policies that achieve the best possible rate of convergence and find that, under certain circumstances, the better rate is obtained by inexpensive gradient methods.en_US
dc.rightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.en_US
dc.titleRate of Convergence Analysis of Discretization and Smoothing Algorithms for Semi-Infinite Minimax Problemsen_US
dc.typeArticleen_US
dc.contributor.departmentOperations Research (OR)


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