HEC Montréal, Canada, May 6 - 8, 2013

2013 Optimization Days

HEC Montréal, Canada, 6 — 8 May 2013

Schedule Authors My Schedule

WA6 Optimisation globale / Global Optimization

May 8, 2013 10:30 AM – 12:10 PM

Location: Mary Husny

Chaired by Jordan Ninin

3 Presentations

  • 10:30 AM - 10:55 AM

    Global Optimization using Contractor Programming

    • Jordan Ninin, presenter, GERAD

    Nowadays, the optimization problems are complex. But, despite the increasing number of solvers, the resolution is always a hard task to merge different kinds of constraints (linear, non-convex or black-box,...) and different kinds of variables (continuous, integer, optimal control,...). The Contractor Programming is a united framework which combines heterogeneous solvers. The principle is based on a Branch-and-Bound using Interval Analysis. Each algorithm is brought to an elementary operation which consists to contract or to prune a box.

  • 10:55 AM - 11:20 AM

    Heuristic Global Optimization via Quick Exploration of the Variable Space

    • John Chinneck, Carleton University
    • Mubashsharul Shafique, presenter, Carleton University

    Many heuristics for global optimization require numerous launches of an expensive local solver. We avoid this by using quick and computationally inexpensive methods (constraint consensus, clustering, simple search) to explore the variable space before choosing a small number of launch points for the local solver. Encouraging empirical results are given.

  • 11:20 AM - 11:45 AM

    Packing Unit Spheres into Three Dimensional Sphere Using VNS

    • Abdulaziz Alkandari, presenter, Public Authority for Applied Education & training
    • Rym M'Hallah, Kuwait University
    • Nenad Mladenovic, Mathematical Institute SANU

    The NP hard optimization problem of packing unit radii spheres into the three dimensional sphere is approximately solved using a variable neighborhood search (VNS) which identifies (near-) global optima by searching the neighborhoods of local minima. VNS obtains neighboring solutions by shaking one or more spheres. It alters the size of a neighborhood every time it fails to find an improving solution.

    Keywords: variable neighborhood search, packing spheres in a cube, non-linear programming, three dimensional packing