A heterogeneous evaluation model for assessing sustainable energy: A Belgian case study

MacArena Espinilla, Da Ruan, Jun Liu, Luis Martínez

    Research outputpeer-review

    Abstract

    Decision makers are increasingly involved in complex real decisions that require multiple viewpoints. A specific case of this fact is the evaluation of sustainable policies related to environment and energy sectors. In this evaluation process, different scenarios are evaluated according to multiple desired criteria that might have different nature. These evaluation processes aim to obtain an overall assessment for each scenario with a complete description of the different related criteria to compare the alternate scenarios for a ranking among them with the goal of identifying the best one. In such complex decision making problems a key problem is the modelling of experts' assessments for each criterion of the scenarios due to the vagueness, uncertainty and nature of such assessments. In this contribution, we propose an evaluation model applied to energy policy selection based on the decision analysis that can manage different types of information (numerical, interval-valued and linguistic) and eventually models linguistically the experts' information with the aim of facilitating the interpretation and keeping accurate results. We apply this model to a case study for evaluating Belgian long-term sustainable energy scenarios.

    Original languageEnglish
    Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
    Place of PublicationBarcelona, Spain
    Pages227-234
    Volume3
    DOIs
    StatePublished - 2010
    Event2010 IEEE World Congress on Computational Intelligence - FUZZ-IEEE 2010, Barcelona
    Duration: 18 Jul 201023 Jul 2010

    Publication series

    Name2010 IEEE World Congress on Computational Intelligence, WCCI 2010

    Conference

    Conference2010 IEEE World Congress on Computational Intelligence
    Country/TerritorySpain
    CityBarcelona
    Period2010-07-182010-07-23

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computational Theory and Mathematics

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