Methods of Nonsmooth Optimization in Stochastic Programming : From Conceptual Algorithms to Real-World Applications

Introduction -- Primer of convex analysis -- Variational analysis -- Linear and nonlinear optimization problems -- Probability and Statistics -- Fundamental modeling questions in stochastic programming -- Adjusting to uncertainty: modeling recourse -- Probability constraints -- Proximal point algorithms for problems with structure -- Cutting-plane algorithms for nonsmooth convex optimization over simple domains -- Bundle methods for nonsmooth convex optimization over simple domains -- Methods for nonlinearly constrained nonsmooth optimization problems -- Methods for nonsmooth optimization with mixed-integer variables -- Methods for nonsmooth nonconvex optimization -- Two-stage stochastic programs -- Progressive decoupling in multistage stochastic programming -- Scenario decomposition with alternating projections -- Methods for multistage stochastic linear programs -- Methods for handling probability.