Computational Sustainability is an interdisciplinary field that aims to develop computational
and mathematical models and methods for decision making concerning
the management and allocation of resources in order to help solve environmental
problems.
This thesis deals with a broad spectrum of such problems (energy efficiency, water
management, limiting greenhouse gas emissions and fuel consumption) giving
a contribution towards their solution by means of Logic Programming (LP) and
Constraint Programming (CP), declarative paradigms from Artificial Intelligence
of proven solidity.
The problems described in this thesis were proposed by experts of the respective
domains and tested on the real data instances they provided. The results are encouraging
and show the aptness of the chosen methodologies and approaches.
The overall aim of this work is twofold: both to address real world problems
in order to achieve practical results and to get, from the application of LP and
CP technologies to complex scenarios, feedback and directions useful for their
improvement