A new framework to generate Lagrangian cuts in multistage stochastic mixed-integer programming

Based on recent advances in Benders decomposition and two-stage stochastic integer programming we present a new generalized framework to generate Lagrangian cuts in multistage stochastic mixed-integer linear programming (MS-MILP). This framework can be incorporated into decomposition methods for MS-MILPs, such as the stochastic dual dynamic integer programming (SDDiP) algorithm. We show how different normalization techniques … Read more

Upper and Lower Bounds for Large Scale Multistage Stochastic Optimization Problems: Application to Microgrid Management

We consider a microgrid where different prosumers exchange energy altogether by the edges of a given network. Each prosumer is located to a node of the network and encompasses energy consumption, energy production and storage capacities (battery, electrical hot water tank). The problem is coupled both in time and in space, so that a direct … Read more