Abstract
Policy making is a very complex task taking into account several aspects related to sustainability, namely impact on the environments, health of productive sectors, economic implications and social acceptance. Optimization methods could be extremely useful for analysing alternative policy scenarios, but should be complemented with several other techniques such as machine learning, agent-based simulation, opinion mining and visualization to come up with an integrated system able to support decision making in the overall policy design life cycle. I will discuss how these techniques could be merged with optimization and I will identity some open research directions.
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Milano, M. (2013). Optimization for Policy Making: The Cornerstone for an Integrated Approach. In: Schulte, C. (eds) Principles and Practice of Constraint Programming. CP 2013. Lecture Notes in Computer Science, vol 8124. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40627-0_1
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DOI: https://doi.org/10.1007/978-3-642-40627-0_1
Publisher Name: Springer, Berlin, Heidelberg
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