The evaluation and selection of recommender systems is a difficult decision making process. This difficulty is partially due to the large diversity of published evaluation criteria in addition to lack of standardized methods of evaluation. As such, a systematic methodology is needed that explicitly considers multiple, possibly conflicting metrics and assists decision makers to evaluate and find...

This paper offered a procedure for ranking the entrepreneurial and innovative indicators using Multi Criteria Decision Making (MCDM), taking into account three individual,organizational and cultural dimensions simultaneously in decision making procedure. Henceforward, by using the Meta synthesis framework, the form of group classification of indicators from afinding’s combination was suggested ...

Abstract— In this paper, a new extended method of multi criteria decision making based on fuzzy-Topsis theory is introduced. fuzzy mcdm algorithm for determining the best choice among all possible choices when the data are fuzzy is also presented. Using a new index leads to procedure for choosing fuzzy ideal and negative ideal solutions directly from the fuzzy data observed alternatives.in this...

a r t i c l e i n f o The classic multiple-criteria decision making (MCDM) model assumes that, when taking a decision, the decision maker has defined a fixed set of criteria and is presented with a clear picture of all available alternatives. The task then reduces to computing the score of each alternative, thus producing a ranking, and choosing the one that maximizes this value. However, most ...

Multiple Criteria Decision Making or multi-attribute (MCDM) problems refer to performing preference decisions (e.g. ranking, ordering, prioritization, selection) over several available alternatives or objects that are characterized by multiple, usually conflicting, attributes or criteria. MCDM techniques have been and are still being encountered in a wide range of human activities, from the pro...

The Fuzzy Analytic Network Process (ANP) is generally used for solving multicriteria decision making (MCDM) problems by considering the pairwise comparison between criteria/sub-criteria, and inner/outer dependencies among criteria. Linguistic expressions are used for experts’ judgements, and these judgements are imprecise and vague. Hence, incorporating fuzziness with multi-criteria decision ma...

An important focus in current research on decision support systems (DSS) is the design of flexible environments to facilitate and support learning about the problem domain by the user. This research uses case-based reasoning to present a symbiotic DSS in which both the user and the DSS learn from each other. The user learns from the DSS (from stored prior problem solutions) and the system learn...

The selection of a strategy to seismically upgrade an existing building is a difficult problem. In fact, several different technologies are available to this aim nowadays. Furthermore, many generally conflicting options have to be considered to assess the performance of each alternative. Decision support systems like the socalled multi-criteria decision-making (MCDM) methods may be useful in ma...

Often data in multi-criteria decision making (MCDM) problems are imprecise and changeable. Therefore, an important step in many applications of MCDM is to perform a sensitivity analysis on the input data. This paper presents a methodology for performing a sensitivity analysis on the weights of the decision criteria and the performance values of the alternatives expressed in terms of the decisio...

ABSTRACT. ––Land suitability assessment in a Geographic Information System (GIS) environment is formulated as a multi-criteria decision making (MCDM) problem. Different MCDM approaches are developed to combine factors in a suitability analysis of land for potential land uses. These MCDM approaches are used to develop a generic suitability index. Approaches include both qualitative and quantitat...