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dc.contributor.authorRoyset, Johannes O.
dc.dateApril 6, 2016
dc.date.accessioned2016-05-16T21:56:32Z
dc.date.available2016-05-16T21:56:32Z
dc.date.issued2016-04-06
dc.identifier.urihttp://hdl.handle.net/10945/48683
dc.descriptionThis paper is in review.en_US
dc.description.abstractApproximation is central to many optimization problems and the supporting theory pro- vides insight as well as foundation for algorithms. In this paper, we lay out a broad framework for quantifying approximations by viewing nite- and in nite-dimensional constrained minimization prob- lems as instances of extended real-valued lower semicontinuous functions de ned on a general metric space. Since the Attouch-Wets distance between such functions quanti es epi-convergence, we are able to obtain estimates of optimal solutions and optimal values through estimates of that distance. In par- ticular, we show that near-optimal and near-feasible solutions are effectively Lipschitz continuous with modulus one in this distance. We construct a general class of approximations of extended real-valued lower semicontinuous functions that can be made arbitrarily accurate and that involve only a nite number of parameters under additional assumptions on the underlying metric space.en_US
dc.format.extent26 p.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.titleApproximations and Solution Estimates in Optimizationen_US
dc.contributor.corporateNaval Postgraduate School (U.S.)en_US
dc.contributor.departmentOperations Research (OR)en_US
dc.subject.authorepi-convergenceen_US
dc.subject.authorAttouch-Wets distanceen_US
dc.subject.authorepi-splinesen_US
dc.subject.authorsolution stabilityen_US
dc.subject.authorapproximation theoryen_US
dc.subject.authornear-optimalityen_US
dc.subject.authornear-feasibilityen_US
dc.subject.authorrate of convergenceen_US


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