Rough set and rule-based multicriteria decision aiding

The aim of multicriteria decision aiding is to give the decision maker a recommendation concerning a set of objects evaluated from multiple points of view called criteria. Since a rational decision maker acts with respect to his/her value system, in order to recommend the most-preferred decision, one must identify decision maker's preferences. In this paper, we focus on preference discovery from data concerning some past decisions of the decision maker. We consider the preference model in the form of a set of "if..., then..." decision rules discovered from the data by inductive learning. To structure the data prior to induction of rules, we use the Dominance-based Rough Set Approach (DRSA). DRSA is a methodology for reasoning about data, which handles ordinal evaluations of objects on considered criteria and monotonic relationships between these evaluations and the decision. We review applications of DRSA to a large variety of multicriteria decision problems

Analysis of the potentials of multi criteria decision analysis methods to conduct sustainability assessment

Sustainability assessments require the management of a wide variety of information types, parameters and uncertainties. Multi criteria decision analysis (MCDA) has been regarded as a suitable set of methods to perform sustainability evaluations as a result of its flexibility and the possibility of facilitating the dialogue between stakeholders, analysts and scientists. However, it has been reported that researchers do not usually properly define the reasons for choosing a certain MCDA method instead of another. Familiarity and affinity with a certain approach seem to be the drivers for the choice of a certain procedure. This review paper presents the performance of five MCDA methods (i.e. MAUT, AHP, PROMETHEE, ELECTRE and DRSA) in respect to ten crucial criteria that sustainability assessments tools should satisfy, among which are a life cycle perspective, thresholds and uncertainty management, software support and ease of use. The review shows that MAUT and AHP are fairly simple to understand and have good software support, but they are cognitively demanding for the decision makers, and can only embrace a weak sustainability perspective as trade-offs are the norm. Mixed information and uncertainty can be managed by all the methods, while robust results can only be obtained with MAUT. ELECTRE, PROMETHEE and DRSA are non-compensatory approaches which consent to use a strong sustainability concept, accept a variety of thresholds, but suffer from rank reversal. DRSA is less demanding in terms of preference elicitation, is very easy to understand and provides a straightforward set of decision rules expressed in the form of elementary “if … then …” conditions. Dedicated software is available for all the approaches with a medium to wide range of results capability representation. DRSA emerges as the easiest method, followed by AHP, PROMETHEE and MAUT, while ELECTRE is regarded as fairly difficult. Overall, the analysis has shown that most of the requirements are satisfied by the MCDA methods (although to different extents) with the exclusion of management of mixed data types and adoption of life cycle perspective which are covered by all the considered approaches

Dominance-based rough set approach and analytic network process for assessing urban transformation scenarios

For half a century, the significant development of intensive farming has led to a massive use of products such as pesticides. The excessive use of these substances has contaminated surface water and groundwater. Drinking water extraction points have also had to be abandoned. Some thirty years ago, in the southwest of France, a group of farmers decided to improve their farming methods, as well as developing new Best Environmental Practices, such as grass strips along streams and riparian forests. By combining the use of ELECTRE TRI-C multi-criteria model with a GIS, we were able to characterise the contribution of each farming area to the risk of surface water contamination with pesticides. We also assessed the effectiveness of different environmental practices. We found that the use of Best Environmental Practices led to a reduction in the risk of pesticides transfer. This methodology re-enforces decision support tools for water resource managers and agricultural and environmental stakeholders

A fuzzy measure of the ability of a real estate capital to increase in value. The real estate decision problem for Ortigia

The valorization processes of real estate capital are strongly influenced by the ability of the different buildings to capture and incorporate some liquidity flows, this capacity, is closely related to the dynamics of the market, of its segments and the single building. The study proposes in this regard, a new methodology, warranting a continuity process with some traditional economic and evaluation approach, using some new tools, such as the developed rough set  by the Operations Research for other issues, but, in this case, that have an instrumental role for the identification of the capacity to increase in value of a real estate capital and to propose a fuzzy measure of this capacity. The study case is that of the market of Ortigia, the historic center of Syracuse

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Electre Methods: Main Features and Recent Developments

We present main characteristics of Electre family methods, designed for multiple criteria decision aiding. These methods use as a preference model an outranking relation in the set of actions - it is constructed in result of concordance and non-discordance tests involving a specific input preference information. After a brief description of the constructivist conception in which the Electre methods are inserted, we present the main features of these methods. We discuss such characteristic features as: the possibility of taking into account positive and negative reasons in the modeling of preferences, without any need for recoding the data; using of thresholds for taking into account the imperfect knowledge of data; the absence of systematic compensation between "gains" and "losses". The main weaknesses are also presented. Then, some aspects related to new developments are outlined. These are related to some new methodological developments, new procedures, axiomatic analysis, software tools, and several other aspects. The paper ends with conclusions

Π5 – Τεχνική έκθεση (βιβλιογραφική ανασκόπηση συνδυασμού μεθόδων τεχνητής νοημοσύνης και πολυκριτήριας ανάλυσης)

Η παρούσα βιβλιογραφική ανασκόπηση επικεντρώνεται στην ανάλυση της σχέσης ανάμεσα σε τεχνικές ΠΑΑ και μεθοδολογίες από το πεδίο της ΤΝ, καθώς και του τρόπου με τον οποίο η ευστάθεια αντιμετωπίζεται στα δύο πεδία. Η καταγραφή αυτή συμβάλει στον εντοπισμό συνεργειών που μπορούν να προκύψουν από την ανάπτυξη διαδικασιών που συνδυάζουν ιδέες, έννοιες και αρχές από τα πεδία της ΠΑΑ και της ΤΝ για την καλύτερη μελέτη της ευστάθειας σε προβλήματα λήψης αποφάσεων. H βιβλιογραφική ανασκόπηση πραγματοποιείται στα πλαίσια διαδικασιών ανάπτυξης μοντέλων αποφάσεων μέσω της αναλυτικής-συνθετικής προσέγγισης (preference disaggregation approach, Jacquet-Lagrèze & Siskos, 2001) της ΠΑΑ, η οποία όπως θα αναλυθεί έχει σημαντικά κοινά στοιχεία με τεχνικές από το χώρο της ΤΝ και ιδιαίτερα με μεθοδολογίες μηχανικής μάθησης (machine learning)