DDSIP implements a number of scenario decomposition algorithms for stochastic linear programs with mixed-integer recourse. Main idea is the Lagrangian relaxation of the nonanticipativity constraints and a branch and bound algorithm to reestablish nonanticipativity. For dual optimization it uses the ConicBundle algorithm of Christoph Helmberg. Mixed-integer subproblems are solved with the CPLEX callable library.
DDSIP supports mean-risk models involving the risk measures expected shortfall below target, excess probabilities, absolute semideviation, worst-case-costs, tail value-at-risk, and standard deviation. Any found bugs should be reported to the authors.
DDSIP was developed by Claus C. Carøe, Ralf Gollmer. Andreas Märkert, and Rüdiger Schultz.
This solver was implemented by Hans Mittelmann and executes at