This paper describes an application of multi-criteria decision making (MCDM) for multi-modal fusion of features in a 3D face recognition system. A decision making process is outlined that is based on the performance of multi-modal features in a face recognition task involving a set of 3D face databases. In particular, the fuzzy interval valued MCDM technique called TOPSIS is applied for ranking...

The present research work deals with a logistic membership function (MF), within non-linear MFs, in finding out fuzziness patterns in disparate level of satisfaction for Multiple Criteria Decision-Making (MCDM) problem. This MF is a modified form of general set of S-curve MF. Flexibility of this MF in applying to real world problem has also been validated through a detailed analysis. An example...

This paper concerns some aspects of uncertainty in a multi-criteria decision-making (MCDM) in the framework of recommendation systems. We try to emphasize the interest of handling uncertainty with possibility distributions in a MCDM process when evaluations are imprecise. We propose to support the recommendation process by managing the propagation of decision-making indicators (location, imprec...

This paper presents an approach to select the best farming strategy considering various criteria. The goal is to help a farmer to take appropriate decision in farming. Two possible alternatives are consideredConventional farming and Organic farming. These farming types are evaluated by MCDM technique taking into account three criteria viz. Productivity, Marketing, and Health-Environment Friendl...

Multiple Criteria Decision Making (MCDM) aims at giving people a knowledge recommendation concerning a set of objects evaluated from multiple preference-ordered attributes. The Superiority and Inferiority Ranking (SIR) is a generation of the well-known outranking approachPROMETHEE, which is an efficient approach for MCDM. As the traditional MCDM approach, however, it faces the obstacle in handl...

This paper proposes the application of Meta-Learning Evolutionary Artificial Neural Network (MLEANN) in selecting flexible manufacturing systems (FMS) from a group of candidate FMS’s. First, multi-criteria decisionmaking (MCDM) methodology using an improved S-shaped membership function has been developed for finding out the “best candidate FMS alternative” from a set of candidate-FMSs. The MCDM...

For ensuring the successful implementation of knowledge management, here raises a critical issue of how companies can better evaluate and select a favorable knowledge management strategy before that implementation. However, selecting a proper knowledge management strategy is a kind of multiple criteria decision-making (MCDM) problem required to consider a large number of complex factors. Unlike...

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...

In multiple criteria decision making (MCDM) methods, the analytic network process (ANP) is used to overcome the problems of interdependence and feedback between criteria or alternatives. The ANP method currently deals with normalization in the supermatrix by assuming each cluster has equal weight. Although the method to normalize the supermatrix is easy, it ignores the different effects among ...