Fuzzy-set decision support for a Belgian long-term sustainable energy strategy

Erik Laes, Gaston Meskens, Da Ruan, Jie Lu, Guangquan Zhang, Fengjie Wu, William D'haeseleer, Raoul Weiler

    Research outputpeer-review

    Abstract

    This chapter addresses the methodological challenges of developing relevant scientific knowledge for a sustainable energy system transition in an innovative way. We argue that scientific contributions to sustainable development do not follow the "linear" procedure from empirical knowledge production to policy advice. Instead, they consist of problem-oriented combinations of explanatory, orientationand action-guiding knowledge. Society and policy makers not only have to be 'provided' with action-guiding knowledge, but also with an awareness of the manner in which this knowledge is to be interpreted, and where the inevitable uncertainties lie. Since the sustainability question is inherently multi-dimensional, participation of social groups is an essential element of a strategy aimed at sustainable development. Multi-criteria decision support provides a platform to accommodate a process of arriving at a judgment or a solution for the sustainability question based on the input and feedback of multiple individuals. At the same time in practice, multi-criteria problems at tactical and strategic levels often involve fuzziness in their criteria and decision makers' judgments. Therefore, we argue in favor of the use of fuzzy-logic based multi-criteria group decision support as a decision support tool for long-term strategic choices in the context of Belgian sustainable energy policy.

    Original languageEnglish
    Title of host publicationIntelligent Decision and Policy Making Support Systems
    EditorsDa Ruan, Klaas Meer, Frank Hardeman
    Place of PublicationHeidelberg, Germany
    PublisherSpringer
    Pages271-296
    Number of pages26
    Edition1
    ISBN (Print)9783540783060
    DOIs
    StatePublished - 2008

    Publication series

    NameStudies in Computational Intelligence
    Volume117
    ISSN (Print)1860-949X

    ASJC Scopus subject areas

    • Artificial Intelligence

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