An improved grey relational analysis as a decision-making method for manufacturing situations
R.V. Rao and
Dron Singh
International Journal of Decision Sciences, Risk and Management, 2010, vol. 2, issue 1/2, 1-23
Abstract:
Decision-makers in the manufacturing sector frequently face the problem of assessing a wide range of alternative options, and selecting one based on a set of conflicting attributes. There is a need for simple, systematic, and logical methods or mathematical tools to guide decision-makers in considering a number of selection attributes and their interrelations and in making good decisions. This paper uses a new multi-attribute decision-making (MADM) method, grey relational analysis (GRA), for solving the deterministic decision-making problems of the manufacturing environment. The method is improved in the present work by integrating with analytic hierarchy process (AHP) and the fuzzy logic. Three examples are presented to illustrate the potential of improved GRA and the results are compared with the results obtained by using other decision-making methods. The comparisons show that the improved GRA is comparatively more logical for solving MADM problems of the manufacturing environment.
Keywords: multiple attribute decision making; MADM; grey relational analysis; GRA; materials selection; rapid prototyping; process selection; plant layout; design selection; layout design; manufacturing; analytical hierarchy process; AHP; fuzzy logic. (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=34668 (text/html)
Access to full text is restricted to subscribers.
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:ids:ijdsrm:v:2:y:2010:i:1/2:p:1-23
Access Statistics for this article
More articles in International Journal of Decision Sciences, Risk and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().