A Progressive Hedging Based Branch-and-Bound Algorithm for Stochastic Mixed-Integer Programs
Semih Atakan (atakanusc.edu)
Abstract: Progressive Hedging (PH) is a well-known algorithm for solving multi-stage stochastic convex optimization problems. Most previous extensions of PH for stochastic mixed-integer programs have been implemented without convergence guarantees. In this paper, we present a new framework that shows how PH can be utilized while guaranteeing convergence to globally optimal solutions of stochastic mixed-integer convex programs. We demonstrate the effectiveness of the proposed framework through computational experiments.
Keywords: multi-stage stochastic mixed-integer convex programming; progressive hedging
Category 1: Stochastic Programming
Citation: University of Southern California.
Entry Submitted: 05/13/2017
Modify/Update this entry
|Visitors||Authors||More about us||Links|
Search, Browse the Repository
Give us feedback
|Optimization Journals, Sites, Societies|