ABSTRACT
A central trend in the optimization community over the past several years has been the steady improvement of general-purpose solvers. A logical next step in this evolution is to combine mixed integer linear programming, constraint programming, and global optimization in a single system. In this talk I describe recent developments in SIMPL, which attempts to implement low-level integration of solution techniques using a high-level modeling language, based on a unifying theoretical framework. I report SIMPL's performance for some problems on which customized integrated methods have shown significant computational advantage. SIMPL matches or surpasses the original codes at a fraction of the implementation effort. It is superior to state-of-the-art MILP and global solvers on most instances, by orders of magnitude on a few. This is joint work with Tallys Yunes and Ionut Aron.
