The use of a preference disaggregation method in energy analysis and policy making
ABSTRACT Following the oil crisis, most developed countries have increasingly implemented measures for energy conservation and fuels substitution aimed at decreasing the energy intensities of their economies. These efforts have been further augmented during the eighties due to growing awareness of adverse effects of energy use on the environment. The measures and their effectiveness differ greatly from country to country, without clear identification of the relevant cause–effect relations. We examine this issue by using a multicriteria decision aid (MCDA) method based on preference disaggregation analysis. The method used is the UTADIS (UTilités Additives DIScriminantes) method that has already been widely applied for financial management. The problem examined in this paper has been formulated following the segmentation approach where a number of countries are grouped into a set of predefined classes according to their energy intensities. The UTADIS method proceeds to the estimation of a set of additive utility functions referring to various indices characterizing the economic and energy structure of each country. The analysis is performed at 3 distinct points in time in order to check for consistency of results and investigate time-dependent phenomena. The results show to what extent each of the examined characteristics influences the countries' energy effectiveness and may be further exploited in energy-policy making. They confirm that the UTADIS method is a powerful tool for examination of a wide range of real decision situations.
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ABSTRACT: Renewable energies are rising as solutions for a sustainable, environmentally friendly and long-term cost effective sources of energies for the future. Renewable energy decision making can be viewed as a multiple criteria decision- making problem with correlating criteria and alternatives. Multi-criteria decision analysis (MCDM) offer a flexible tool that is able to handle and bring together a wide range of variables and thus offer useful assistance to the decision maker in mapping out the situation. MCDM methods can be divided into two categories, multi-objective decision making (MODM) and multi-attribute decision making (MADM). A review of 90+ published papers of MCDM analysis in the renewable energy field is presented in this paper. Classification of both application area as well as methodology used are summarized. Analysis reveals that AHP is the most used of all MCDM methodologies.01/2011;
Article: COMMENTS ON THE OCTUPOLE MODE
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ABSTRACT: We address the problem of sorting alternatives evaluated by multiple criteria among preference-ordered classes. We develop an interactive probabilistic sorting approach by calculating the probability of an alternative being in each class and assign alternatives to classes keeping the probability of incorrect assignments below a specified small threshold value. The decision maker is occasionally required to place alternatives to classes. We update the probabilities for unassigned alternatives in light of the new information and repeat the procedure until all alternatives are classified. To the best of our knowledge, this is the first sorting approach that uses an explicit probability of classifying alternatives consistent with the underlying preference structure of the decision maker. We demonstrate our approach to sort MBA programs.IIE Transactions 01/2012; · 1.29 Impact Factor