Wright, Stephen E., 1962-2009-10-052009-10-051990b2583665124331621http://hdl.handle.net/1773/5751Thesis (Ph. D.)--University of Washington, 1990Large-scale problems in convex optimization often can be reformulated in primal-dual (minimax) representations having special decomposition properties. Approximation of the resulting high-dimensional problems by restriction to low-dimensional subspaces leads to a family of minimax problems dependent on a parameter. The continuity and convergence properties of this dependence are explored in this dissertation. Examples in optimal control and stochastic programming are considered in which discretizations give rise to large-scale optimization problems. A possible approach to the numerical solution of the discretized problems is described, as well as details of its computer implementation.iii, 100 p.en-USCopyright is held by the individual authors.Theses--MathematicsThesis