Results for the 2024 MiniZinc Challenge have now been announced!
David Hemmi

David Hemmi

david.hemmi@monash.edu
Monash University

Stochastic MiniZinc, efficient algorithms for stochastic combinatorial problems.

Publications on MiniZinc by David Hemmi

  • David Hemmi, Guido Tack, and Mark Wallace. 2018.
    A Recursive Scenario Decomposition Algorithm for Combinatorial Multistage Stochastic Optimisation Problems.
    Abstract
    Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence and Thirtieth Innovative Applications of Artificial Intelligence Conference and Eighth AAAI Symposium on Educational Advances in Artificial Intelligence AAAI Press.
  • David Hemmi, Guido Tack, and Mark Wallace. 2017.
    Scenario-Based Learning for Stochastic Combinatorial Optimisation.
    Abstract
    Integration of AI and OR Techniques in Constraint Programming: 277—292. Springer International Publishing.