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.

To solve decision problems related to sustainability, MCDA (Multi-Criteria Decision Analysis) methods are commonly used. However, from the methodological and practical perspective of sustainability assessment, MCDA methods have some shortcomings. To address this, the PROSA (PROMETHEE for Sustainability Assessment) method was designed. In contrast to other MCDA methods, PROSA is characterized by a lower degree of criteria compensation, thus supporting the strong sustainability paradigm. However, PROSA has some imperfections related to, among other things, its taking into consideration only basic sustainability dimensions and lack of criteria hierarchy handling. This article proposes a generalization of the PROSA method towards handling detailed criteria and their groups, while at the same time increasing the clarity of the computational procedure. Additionally, a new analytical tool called PROSA GAIA (Geometrical Analysis for Interactive Assistance) was developed, making it possible to perform descriptive analyses of decision problems. The practical advancements of the proposed method were illustrated using a reference case covering the sustainable decision making area, and were compared to other MCDA methods. The obtained research results clearly show that the generalized PROSA handles the strong sustainability paradigm better than its classical version, while at the same time providing the decision-maker with more possibilities to analyse a decision problem and its solution.

This data article describes the analysis of 56 MCDA (Multi-Criteria Decision Analysis) methods in regards to 9 decision-making problem characteristics structured into 3 levels. The impact of uncertainty in decision-making problem description on MCDA method selection is studied. 450,000 possible descriptions of a decision problem were studied, resulting in sets of rules which can serve as input to uncertainty-aware MCDA method selection decision support systems. Comprehensive analyses of the obtained rule sets are provided. An exemplary decision support system based on the presented data was created and is available at http://www.mcda.it. Moreover the technical documentation needed to create and expand such system is provided in this data article. The data and system can be easily extended and the authors invite all researchers to contribute.

Increasing the popularity of electric vehicles is one way of reducing greenhouse gas emissions and making the economy more sustainable. In Poland, the use of electric vehicles is to be increased by the adoption of the Act on Electromobility and Alternative Fuels. This Act obliges local government units and state administration to expand the electric vehicle fleet. The expansion of the fleet should be carried out on a planned basis, based on rational decisions supported by economic analyses. Therefore, the aim of this article is to provide a recommendation of an electric vehicle that meets the needs of local and state administration to the greatest extent possible. The aim has been achieved using the multi-criteria decision analysis method called PROSA-C (PROMETHEE for Sustainability Assessment—Criteria) combined with the Monte Carlo method. The PROSA-C method allows promoting more sustainable vehicles with high technical, economic, environmental and social parameters. The Monte Carlo method, on the other hand, is a stochastic simulation tool that allows for taking into account the uncertainty of parameters describing vehicles. As a result of the research, the most and least attractive vehicles were identified from the perspective of the needs of local government units and state administration. Moreover, the conducted research allowed confirming the effectiveness and usefulness of the research methodology proposed in the article and the procedural approach combining the PROSA-C and Monte Carlo methods.