a b s t r a c tMulti-Criteria Decision Analysis (MCDA) methods are widely used in various fields and disciplines. While most of the research has been focused on the development and improvement of new MCDA methods, relatively limited attention has been paid to their appropriate selection for the given decision problem. Their improper application decreases the quality of recommendations, as different MCDA methods deliver inconsistent results. The current paper presents a methodological and practical framework for selecting suitable MCDA methods for a particular decision situation. A set of 56 available MCDA methods was analysed and, based on that, a hierarchical set of methods' characteristics and the rule base were obtained. This analysis, rules and modelling of the uncertainty in the decision problem description allowed to build a framework supporting the selection of a MCDA method for a given decision-making situation. The practical studies indicate consistency between the methods recommended with the proposed approach and those used by the experts in reference cases. The results of the research also showed that the proposed approach can be used as a general framework for selecting an appropriate MCDA method for a given area of decision support, even in cases of data gaps in the decision-making problem description. The proposed framework was implemented within a web platform available for public use at www.mcda.it.Please cite this article as: J. W ątróbski et al., Generalised framework for multi-criteria method selection, Omega (2018), https://doi.

Atmospheric emissions of anthropogenic origin are one of the most important problems in cities. A particularly discrete ecological footprint in urban environment is made by urban freight transport. This problem has become the key challenge for all stakeholder groups involved in freight transport in urban areas. Over the recent years, there has been a growing interest in using alternative fuel vehicles in urban logistics, including those equipped with electric drive systems. This paper presents a multi-criteria analysis (MCA) of selected electric vehicles (EVs) in the context of their application for the purposes of deliveries in cities. In methodological terms, we present a unique MCA-based approach for evaluation of Electric Freight Vehicles (EFVs). A successful attempt is made to build a multistep MCA procedure based on two carefully selected MCDA methods (PROMETHEE II and fuzzy TOPSIS) to handle both certain and uncertain data sets in a single decision process. In practical terms, we successfully demonstrate the usefulness of the proposed approach by creating a set of decision maker's preference models (based on certain and uncertain data) of carefully selected EFVs and provide sensitivity and robustness analyses of the obtained solutions.

Abstract:Wind is the most used renewable energy source (RES) in the European Union and Poland. Due to the legal changes in the scope of RES in Poland, there are plans to develop offshore wind farms at the expense of onshore ones. On the other hand, the success of an offshore wind farm is primarily determined by its location. Therefore, the aim of this study is to select offshore wind farm locations in Poland, based on sustainability assessment, which is an inherent aspect of RES decision-making issues. To accomplish the objectives of this research, PROSA (PROMETHEE for Sustainability Assessment) method, a new multi-criteria method is proposed. Like PROMETHEE (Preference Ranking Organization METHod for Enrichment Evaluation), PROSA is transparent for decision makers and is easy to use; moreover, it provides the analytical tools available in PROMETHEE, i.e., the sensitivity and GAIA (Geometrical Analysis for Interactive Assistance) analyses. However, PROSA is characterized by a lower degree of criteria compensation than PROMETHEE. Thus, it adheres in a higher degree to the strong sustainability paradigm. The study also compared the solutions of the decision problem obtained with the use of PROSA and PROMETHEE methods. The compared methods demonstrated a high concurrence of the recommended decision-making variant of location selection, from methodological and practical points of view. At the same time, the conducted research allowed to confirm that the PROSA method recommends more sustainable decision-making variants, and that the ranking it builds is less sensitive to changes in criteria weights. Therefore, it is more stable than the PROMETHEE-based ranking.

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