Place: 4274 Chamberlin (Refreshments will be served)
Speaker: Jim Luedtke, UW Department of Industrial Engineering
Abstract: Stochastic optimization is a branch of mathematical optimization concerned with helping make design, planning, and operation decisions in the face of uncertain outcomes or data. Example applications of stochastic optimization include: planning power generation in systems with uncertainty in wind outputs and rainfall (which effects hydro-reservoir levels); deciding order quantities at a retailer with uncertain customer demands; and making financial investments without knowing the returns the different investment options will yield. I will provide an overview of the field stochastic optimization, with a bias towards topics related to my research. I will focus on discussing different types of models and when they might be useful, and, time permitting, will overview some of the solution approaches.