Measurement of Level-of-Satisfaction of Decision Maker in Intelligent Fuzzy-MCDM Theory: A Generalized Approach
Pandian Vasant,
Arijit Bhattacharya and
Ajith Abraham
Additional contact information
Pandian Vasant: Universiti Teknologi Petronas
Arijit Bhattacharya: Dublin City University, Glasnevin
Ajith Abraham: Norwegian University of Science and Technology
A chapter in Fuzzy Multi-Criteria Decision Making, 2008, pp 235-261 from Springer
Abstract:
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.
Keywords: Decision support system; level-of-satisfaction in MCDM (search for similar items in EconPapers)
Date: 2008
References: Add references at CitEc
Citations: View citations in EconPapers (2)
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-76813-7_9
Ordering information: This item can be ordered from
http://www.springer.com/9780387768137
DOI: 10.1007/978-0-387-76813-7_9
Access Statistics for this chapter
More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().