Modeling Principles¶

Hexaly Optimizer is a new kind of hybrid optimization solver. Its modeling interface is nonlinear and set-oriented. In a sense, Hexaly unifies and extends modeling concepts from mixed-linear programming, nonlinear programming, and constraint programming. Under the hood, Hexaly combines various exact and heuristic optimization methods, such as branch-and-bound, automatic Dantzig-Wolfe reformulation, column and row generation, propagation methods, local search, direct search, and surrogate modeling techniques.

This section details Hexaly’s best modeling practices: how to take advantage of its set-based formalism to achieve the best possible performance, how to distinguish decisions from intermediate expressions, when to use external and black-box functions, how to migrate from MIP to Hexaly, and so on.