Detection of level of satisfaction and fuzziness patterns for MCDM model with modified flexible S-curve MF

نویسندگان

  • Pandian Vasant
  • Arijit Bhattacharya
  • Bijan Sarkar
  • Sanat Kumar Mukherjee
چکیده

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 illustrating an MCDM model applied in an industrial engineering problem has been considered to demonstrate the veracity of the proposed technique. The approach presented here provides feedback to the decision maker, implementer and analyst and gives a clear indication about the appropriate application and usefulness of the MCDM model. The key objective of this paper is to guide decision makers in finding out the best candidate-alternative with higher degree of satisfaction with lesser degree of vagueness under tripartite fuzzy environment. # 2006 Elsevier B.V. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Neuro-fuzzy Approximation of Multi-criteria Decision-making Qfd Methodology

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...

متن کامل

Flexible Manufacturing System Selection under Disparate Level-of-Satisfaction of Decision Maker using Intelligent Fuzzy-MCDM Model

This Chapter outlines an intelligent fuzzy-MCDM model for appropriate selection of Flexible Manufacturing System (FMS) in conflicting criteria environment. A holistic methodology has been developed for finding out the “optimal FMS” from a set of candidate-FMSs. This method trade-offs among various parameters, viz., design parameters, economic considerations, etc., affecting the FMS selection pr...

متن کامل

Fms Selection under Disparate Level- Of-satisfaction of Decision Making Using an Intelligent Fuzzy-mcdm Model

This chapter outlines an intelligent fuzzy multi-criteria decision-making (MCDM) model for appropriate selection of a flexible manufacturing system (FMS) in a conflicting criteria environment. A holistic methodology has been developed for finding out the “optimal FMS” from a set of candidate-FMSs. This method of trade-offs among various parameters, viz., design parameters, economic consideratio...

متن کامل

Measurement of Level-of-Satisfaction of Decision Maker in Intelligent Fuzzy-Multi-criteria Decision Making Theory: A Generalised Approach

This chapter aims to delineate measurement of level-of-satisfaction during decision making under intelligent fuzzy environment. Before proceeding with the multi-criteria decisionmaking model (MCDM), we attempt to build a co-relation among decision support systems (DSS), decision theories and fuzziness of information. The so-relation shows the necessity of incorporating decision makers’ (DM) lev...

متن کامل

Measurement of Level-of-Satisfaction of Decision Maker in Intelligent Fuzzy-MCDM theory: A Generalised Approach

The earliest definitions of decision support systems (DSS) identify DSS as systems to support managerial decision makers in unstructured or semiunstructured decision situations. They are also defined as a computer-based information systems used to support decision-making activities in situations where it is not possible or not desirable to have an automated system perform the entire decision pr...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Appl. Soft Comput.

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2007