Abstract
Stochastic Decomposition (SD) is a randomized version of Benders’ decomposition for the solution of two stage stochastic linear programs with recourse. It combines a recursive sampling scheme within a decomposition-coordination framework in which the algorithm alternates between a master program and. a subprogram. The master program represents a piecewise linear approximation in which each cut is obtained by solving one linear subproblem, and then performing a series of updates based on previously generated outcomes. Using recursive updates, we devise an efficient computer implementation that allows us to address very large two stage stochastic programs with recourse. We report our computational experience with some very large stochastic programs that arise in aircraft fleet scheduling and telecommunications network planning.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
