Risk Management Collaboratory - Constraint Programming and Stochastic Optimization


Research Objectives

  • Explore new directions for multi-stage stochastic optimization by exploiting and developing new constraint programming (CP) techniques, such as stochastic CP or event-driven probabilistic CP
  • Compare and possibly integrate constraint programming and mathematical programming techniques to address large multi-stage stochastic optimization problems
  • Investigate the use of stochastic approximation techniques in the context of CP
  • Extend stochastic constraint programming to handle imprecise probabilities

Short-term Activities

  • Finalize case study and on risk-aware production planning in the pharmaceutical industry sector.
  • Analysis of different risk measures and decision structures and their role for the complexity of the decision problem.
  • Computational tests of different MIP and SCP formulations regarding solution quality and computation time.