Challenges for Constraint Reasoning and Optimization in Computational Sustainability
Computational Sustainability is a new emerging research field with the overall goal of studying and providing solutions to computational problems for balancing environmental, economic, and societal needs for a sustainable future. I will provide examples of challenge problems in Computational Sustainability, ranging from wildlife preservation and biodiversity, to balancing socio-economic needs and the environment, to large-scale deployment and management of renewable energy sources, highlighting overarching computational themes in constraint reasoning and optimization and interactions with machine learning, and dynamical systems. I will also discuss the need for a new approach to study such challenging problems in which computational problems are viewed as “natural” phenomena, amenable to a scientific methodology in which principled experimentation, to explore problem parameter spaces and hidden problem structure, plays as prominent a role as formal analysis.
Unable to display preview. Download preview PDF.
- 1.Gomes, C., Selman, B.: The science of constraints. Constraint Programming Letters 1(1) (2007)Google Scholar
- 2.IPCC. Fourth assessment report (AR4). Technical report, United Nations Intergovernmental Panel on Climate Change, IPCC (2007)Google Scholar
- 3.UNEP. Our common future. Published as annex to the General Assembly document A/42/427, Development and International Cooperation: Environment. Technical report, United Nations Environment Programme, UNEP (1987)Google Scholar
- 4.UNEP. Global environment outlook 4 (GEO4). Technical report, United Nations Environment Programme, UNEP (2007)Google Scholar