Alejandro Marcos Alvarez

Online Learning for Strong Branching Approximation in Branch-and-Bound

  • Quentin Louveaux
  • Alejandro Marcos Alvarez
  • Louis Wehenkel
    • Categories (Mixed) Integer Linear Programming, Branch and Cut Algorithms, Data-Mining Tags , ,

    We present an online learning approach to variable branching in branch-and-bound for mixed-integer linear problems. Our approach consists in learning strong branching scores in an online fashion and in using them to take branching decisions. More specifically, numerical scores are used to rank the branching candidates. If, for a given variable, the learned approximation is … Read more

    Machine Learning to Balance the Load in Parallel Branch-and-Bound

  • Quentin Louveaux
  • Alejandro Marcos Alvarez
  • Louis Wehenkel
    • Categories Branch and Cut Algorithms, Data-Mining

    We describe in this paper a new approach to parallelize branch-and-bound on a certain number of processors. We propose to split the optimization of the original problem into the optimization of several subproblems that can be optimized separately with the goal that the amount of work that each processor carries out is balanced between the … Read more