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    A cumulative belief degree approach for group decision-making problems with heterogeneous information
    (Wiley, 2019) Ervural, Bilal; Kabak, Ozgur
    In some complex group decision-making (GDM) problems, the information needing to be processed may be heterogeneous. This may involve consideration of objective and subjective criteria by experts who have their own particular set of criteria, their own preference format for assessing alternatives under these criteria, and who may themselves be assigned differing importance weights as experts. This paper presents a cumulative belief degree approach to cope with heterogeneous information in multiple attribute GDM problems. The proposed approach focuses to aggregate subjective expert assessments and objective criteria that are presented in various representation formats and scales. The methodology employs transformation formulae for several preference representation scales to belief structure, including 2-tuple representation, classical fuzzy sets, hesitant fuzzy sets, and intuitionistic fuzzy sets. Aggregation formulae are proposed to combine expert criteria evaluations and find a collective preference. A consensus degree is calculated for measuring the agreement between the experts. An illustrative example is presented to clarify the steps of the methodology, and validity of the approach is assured through comparative analysis with the existing methods.
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    Long-term policy evaluation: Application of a new robust decision framework for Iran's energy exports security
    (Pergamon-Elsevier Science Ltd, 2018) Alipour, Mohammad; Hafezi, Reza; Ervural, Bilal; Amin, Mohamad; Kabak, Ozgur
    The objective of this research is to assess long-term energy security policy under uncertain environment. Uncertainty is an integral part of the energy policy analysis in long-term planning, in particular for energy-exporting countries seeking to secure sustainable export revenues. This study proposes a framework to evaluate energy export policy at the strategic level by addressing inherent uncertainties exist in energy-exporting countries. Seven criteria (political, economic, social, technological, legal, environmental, and robustness) are considered to appraise the identified energy export security alternatives. A new hybrid Multi-Criteria Decision-Making (MCDM) model is proposed based on intuitionistic fuzzy sets suitable for uncertain judgments that integrates Intuitionistic Fuzzy Analytic Hierarchy Process (IFAHP) and the Cumulative Belief Degree (CBD) methods. CBD, which is strengthened by IFAHP in determining criteria weights, allows experts to freely evaluate alternatives in various formats and can successfully deal with missing judgments by experts in case of doubt, eligibility or lack of information. Scenario planning is also incorporated into the decision-making process by determining four realistic projections. As a case study, the proposed framework is applied to analyze Iran's energy export security. Results suggest that natural gas has the highest export priority while petroleum products (excluding gasoline) stand last in all scenarios. (C) 2018 Elsevier Ltd. All rights reserved.