Lagrangian Dual Decision Rules for Multistage Stochastic Mixed Integer Programming

Описание: (28 septembre 2021 / September 28, 2021) Atelier Optimisation sous incertitude / Workshop: Optimization under uncertainty

Merve Bodur (University of Toronto, Canada)
Lagrangian Dual Decision Rules for Multistage Stochastic Mixed Integer Programming

Résumé / Abstract: We propose Lagrangian dual decision rules that yield a new approximation approach for multi-stage stochastic mixed integer programming problems. We investigate techniques for using these decision rules to obtain bounds on the optimal value as well as primal feasible policies; and compare the strength of the relaxation from different techniques. Numerical results will be presented to illustrate the quality of the obtained bounds and policies.