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Thesis

Integration of rationale management with multi-criteria decision analysis, probabilistic forecasting and semantics: application to the UK energy sector

Abstract:

This thesis presents a new integrated tool and decision support framework to approach complex problems resulting from the interaction of many multi-criteria issues. The framework is embedded in an integrated tool called OUTDO (Oxford University Tool for Decision Organisation). OUTDO integrates Multi-Criteria Decision Analysis (MCDA), decision rationale management with a modified Issue-Based Information Systems (IBIS) representation, and probabilistic forecasting to effectively capture the essential reasons why decisions are made and to dynamically re-use the rationale. In doing so, it allows exploration of how changes in external parameters affect complicated and uncertain decision making processes in the present and in the future.

Once the decision maker constructs his or her own decision process, OUTDO checks if the decision process is consistent and coherent and looks for possible ways to improve it using three new semantic-based decision support approaches. For this reason, two ontologies (the Decision Ontology and the Energy Ontology) were integrated into OUTDO to provide it with these semantic capabilities. The Decision Ontology keeps a record of the decision rationale extracted from OUTDO and the Energy Ontology describes the energy generation domain, focusing on the water requirement in thermoelectric power plants.

A case study, with the objective of recommending electricity generation and steam condensation technologies for ten different regions in the UK, is used to verify OUTDO’s features and reach conclusions about the overall work.

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Institution:
University of Oxford
Division:
MPLS
Department:
Engineering Science
Research group:
Systems Engineering Group
Oxford college:
St Edmund Hall
Role:
Author

Contributors

Division:
MPLS
Department:
Engineering Science
Role:
Supervisor



Publication date:
2013
DOI:
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK

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