Abstract
In 2004, Jean-Francois Puget presented [2] an analysis of the “simplicity of Use” of Constraint Programming from which he articulated a series of challenges to make Constraint Programming systems accessible and easier to use. The core of the argument was a contrast between mathematical programming and constraint programming tools. Mathematical programming adopts a model and run paradigm, rely on a simple vocabulary to model problems (i.e., linear constraints), support standard formats for sharing models and benefit from extensive documentation on how to model [5]. Constraint programming features a model and search paradigm, rich modeling languages with combinatorial objects and has a distinctive flavor of programming. While it can be construed as CP’s Achilles’ heel, it is also its most potent strength and is supported by modeling aids [3,4]. The very existence of sophisticated parameter tuning solutions for SAT solvers and Math Programming solvers to determine ideal parameters (e.g., ParamILS [1]) certainly cast a major shadow on the potency of the model and run mantra that is evolving into model and search for the right parameters.
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Michel, L.D. (2012). Constraint Programming and a Usability Quest. In: Milano, M. (eds) Principles and Practice of Constraint Programming. CP 2012. Lecture Notes in Computer Science, vol 7514. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33558-7_1
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