To be held in Québec City, Canada from 8-12th October 2012

[École Polytechnique de Montréal]

A smart grid is the combination of a traditional power distribution system with two-way communication between suppliers and consumers. The effective use of this communication is expected to deliver energy savings, cost reductions, and increased reliability and security. However, smart grids introduce important challenges in the management of the power system, such as integrating renewable energy sources and incorporating demand-management approaches.

We will discuss how optimization-based techniques are being used to overcome some of these challenges and speculate on how constraint programming could also play a role.

[University of Connecticut]

In 2004, Jean-Francois Puget presented 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. 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. The very existence
of sophisticated parameter tuning solutions for SAT solvers and Math
Programming solvers to determine ideal parameters (e.g., ParamILS)
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*.

Accessibility to CP technology is a legit concern and the appeal of turnkey
solutions cannot be underestimated. CP tools are extremely pliable and
uniquely adapted to classes of problems where all else fails. Retaining CP's
flexibility while delivering *model and run* solutions suitable for a large number
of situations is the position adopted here.

This talk explores developments and solutions to the apparent quandary. Specifically, it explores automatic search for Constraint-Based Local Search, Scheduling, and finite-domain systems, generic black-box search procedures, automatic parallelization and assisted hybridization.

[Cork Constraint Computation Centre, University College Cork, Ireland]

Constraint programming has become an important technology for solving hard combinatorial problems in a diverse range of application domains. It has its roots in artificial intelligence, mathematical programming, operations research, and programming languages. In this talk we will discuss a number of challenging application domains for constraint programming, and the technical challenges that these present to the research community.