D. Bongartz

MUSE-BB: A Decomposition Algorithm for Nonconvex Two-Stage Problems using Strong Multisection Branching

  • Marco Langiu
  • Manuel Dahmen
  • D. Bongartz
  • Alexander Mitsos
    • Categories Global Optimization, Parallel Algorithms, Stochastic Programming Tags , , , ,

    \(\) We present MUSE-BB, a branch-and-bound (B&B) based decomposition algorithm for the deterministic global solution of nonconvex two-stage stochastic programming problems. In contrast to three recent decomposition algorithms, which solve this type of problem in a projected form by nesting an inner B&B in an outer B&B on the first-stage variables, we branch on all … Read more

    Global Dynamic Optimization with Hammerstein-Wiener Models Embedded

  • D. Bongartz
  • Alexander Mitsos
  • Jaromił Najman
  • C. D. Kappatou
  • S. Sass
    • Categories Global Optimization Theory Tags , , , ,

    Hammerstein-Wiener models constitute a significant class of block-structured dynamic models, as they approximate process nonlinearities on the basis of input-output data without requiring identification of a full nonlinear process model. Optimization problems with Hammerstein-Wiener models embedded are nonconvex, and thus local optimization methods may obtain suboptimal solutions. In this work, we develop a deterministic global … Read more