Margarita P Castro

Markov Chain-based Policies for Multi-stage Stochastic Integer Linear Programming with an Application to Disaster Relief Logistics

  • Margarita P Castro
  • Merve Bodur
  • Yongjia Song
    • Categories (Mixed) Integer Linear Programming, Stochastic Programming Tags , , , ,

    We introduce an aggregation framework to address multi-stage stochastic programs with mixed-integer state variables and continuous local variables (MSILPs). Our aggregation framework imposes additional structure to the integer state variables by leveraging the information of the underlying stochastic process, which is modeled as a Markov chain (MC). We demonstrate that the aggregated MSILP can be … Read more

    Decision Diagrams for Discrete Optimization: A Survey of Recent Advances

  • Margarita P Castro
  • Andre Augusto Cire
  • J. Christopher Beck
    • Categories Combinatorial Optimization, Integer Programming, Network Optimization Tags ,

    In the last decade, decision diagrams (DDs) have been the basis for a large array of novel approaches for modeling and solving optimization problems. Many techniques now use DDs as a key tool to achieve state-of-the-art performance within other optimization paradigms, such as integer programming and constraint programming. This paper provides a survey of the … Read more

    A Combinatorial Cut-and-Lift Procedure with an Application to 0-1 Chance Constraints

  • J. Christopher Beck
  • Margarita P Castro
  • Andre Augusto Cire
    • Categories 0-1 Programming, Cutting Plane Approaches, Second-Order Cone Programming Tags , , ,

    Cut generation and lifting are key components for the performance of state-of-the-art mathematical programming solvers. This work proposes a new general cut-and-lift procedure that exploits the combinatorial structure of 0-1 problems via a binary decision diagram (BDD) encoding of their constraints. We present a general framework that can be applied to a large range of … Read more