Measurement of level-of-satisfaction of decision maker in intelligent fuzzy-MCDM theory: A generalized approach

Pandian Vasant, Arijit Bhattacharya, Ajith Abraham

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Citations (Scopus)

Abstract

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 process. This chapter aims to delineate measurement of level-of-satisfaction during decision making under an intelligent fuzzy environment. Before proceeding with the multi-criteria decision making model (MCDM), authors try to build a co-relation among DSS, decision theories, and fuzziness of information. The co-relation shows the necessity of incorporating decision makers’ level-of-satisfaction in MCDM models. Later, the authors introduce an MCDM model incorporating different cost factor components and the said level-of-satisfaction parameter. In a later chapter, the authors elucidate an application as well as validation of the devised model. The strength of the proposed MCDM methodology lies in combining both cardinal and ordinal information to get eclectic results from a complex, multi-person and multi-period problem hierarchically.

Original languageEnglish
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer International Publishing AG
Pages235-261
Number of pages27
ISBN (Print)978-0-387-76812-0
DOIs
Publication statusPublished - 1 Jan 2008
Externally publishedYes

Publication series

NameSpringer Optimization and Its Applications
Volume16
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

Keywords

  • Decision support system
  • Level-of-satisfaction in MCDM

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