Journées de l'optimisation 2017
HEC Montréal, 810 mai 2017
1^{er} Atelier Canadien sur l'optimisation des soins de santé (CHOW)
HEC Montréal, 1011 mai 2017
JOPT2017
HEC Montréal, 8 — 11 mai 2017
TD1 Exposé magistral 3 / Tutorial 3
9 mai 2017 15h30 – 17h10
Salle: Banque CIBC
Présidée par Leandro Coelho
1 présentation

15h30  17h10
Modeling and optimizing operations research problems with LocalSolver
In this tutorial, we introduce LocalSolver, a heuristic solver for largescale optimization problems. The optimization model can be provided as a classic mathematical problem as LocalSolver is not restricted to a specific structure and supports most of the common mathematical operators. Decisions can be booleans, integers or continuous. The solver is designed to find good solutions for large problems in short running times. The main part of the tutorial deals with the new features of LocalSolver 7.
LocalSolver 6.5 introduced high level decisions based on sets that allow users to write simpler models. These decisions are based on the notion of list inspired from Constraint Programming SetBased Variables. The new models are more compact for the solver and solutions can be found for larger instances. LocalSolver 7 adds new features to simplify the usage of variable length lists so that fixed arrays and variable lists are similar for the user. These new features are particularly useful to model routing and scheduling problems in just a few lines.
LocalSolver 7 also introduces new large neighborhood for numerical optimization based on a better exploitation of the model. These new intensification moves accelerate the convergence speed to local optima in nonlinear continuous optimization and leave more time for diversification.
The conclusion of the tutorial is about the future developments of LocalSolver, namely the extensions of set based models, the computation of lower bounds on generic models and the detection of global structures.