نتایج جستجو برای: criteria decision making mcdm
تعداد نتایج: 768519 فیلتر نتایج به سال:
There has been a growing interest and activity in the area of multiple criteria decision making (MCDM), especially in the last 20 years. Modeling and optimization methods have been developed in both crisp and fuzzy environments. The overwhelming majority of approaches for finding best compromise solutions to MCDM problems do not make use of the interdependences among the objectives. However, as...
Numerous companies are expecting their knowledge management (KM) to be performed effectively in order to leverage and transform the knowledge into competitive advantages. However, here raises a critical issue of how companies can better evaluate and select a favorable KM strategy prior to a successful KM implementation. The KM strategy selection is a kind of multiple criteria decision-making (M...
The evaluation of clustering algorithms is intrinsically difficult because of the lack of objective measures. Since the evaluation of clustering algorithms normally involves multiple criteria, it can be modeled as a multiple criteria decision making (MCDM) problem. This paper presents an MCDM-based approach to rank a selection of popular clustering algorithms in the domain of financial risk ana...
Hesitant fuzzy set (HFS), which can be accurately and perfectly described in terms of the opinions of decision makers, is considered as a powerful tool to express uncertain information in the process of multi-attribute decision making (MADM) problems. The core of the HFS is the hesitant fuzzy element (HFE).This paper developed a method, which using the interval probabilistic hesitant fuzzy elem...
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...
The aim of this study was to provide an analytical tool to evaluate and select the best supplier(s)/vendor(s) in fuzzy environment for Television (TV) manufacturing organization. A hierarchy through which decision makers can bring about a comparison among the suppliers was worked out and software for the same was developed. The methodology for selection was based upon multiple criteria decision...
Primary school selection is actually a decision making problem that should be supported with several source of information. Parents usually handle this problem in an unstructured manner which is indeed a fuzzy mental ranking of schools with respect to the effectiveness. In this study, an analytical hybrid multiple criteria decision making (MCDM) model is proposed and explained with details for ...
The increasing complexity of modern computer systems emerges as a real challenge for both the users and the designers. According to the innovative vision of Organic Computing systems, the system components will profit from their autonomy to perform a self-organization, and subsequently, to reach a high degree of adaptivity. The goal of this thesis is to investigate the vision of Organic Computi...
This chapter demonstrates how a neuro-fuzzy approach could produce outputs of a further-modified multi-criteria decision-making (MCDM) quality function deployment (QFD) model within the required error rate. The improved fuzzified MCDM model uses the modified S-curve membership function (MF) as stated in an earlier chapter. The smooth and flexible logistic membership function (MF) finds out fuzz...
This paper presents a structured methodology for Information Systems (IS) outsourcing decision problem. The problem of selection among candidate information systems of the IS can be formulated as Multi criteria decision making (MCDM) techniques. Thus, this paper proposes a fuzzy group decision making process to evaluate and select the appropriate Information System Project (ISP) based on fuzzy ...
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