Computational Constraint Models for Decision Support and Holistic Solution Design

The paradigm of constraint reasoning aims at modeling and solving combinatorial search problems. The methodology and principle of such models are based on relationships among data and variables, specifically as constraints that must hold for a solution to answer a decision or optimization problem. The relationships can be dependencies of any kind: geographical, engineering, environmental, or economic. Constraint models have been developed to provide proactive analysis of some climate change issues, such as investment planning in renewable energies over a given horizon. The challenge of computerized constraint models is their reliability and effectiveness to be used for real-world implementation. This is feasible if: (1) the modeling approach taken is holistic and specifies the complexity of real-world scenarios, and (2) the users feel involved and become actual actors in the decision process. Constraint models facilitate a holistic approach by focusing on the solution model, and allowing heterogeneous data, variables, and constraint types to be modeled independently of their solving. This chapter gives an overview of such approaches to foster the implementation of climate change solutions.