Welcome to Central Library, SUST
Amazon cover image
Image from Amazon.com
Image from Google Jackets

Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods [electronic resource] : Volume 2 / by R. Venkata Rao.

By: Contributor(s): Material type: TextTextSeries: Springer Series in Advanced ManufacturingPublisher: London : Springer London : Imprint: Springer, 2013Description: XIV, 294 p. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781447143758
Subject(s): Additional physical formats: Printed edition:: No titleDDC classification:
  • 658.5 23
LOC classification:
  • TA177.4-185
Online resources:
Contents:
1. Multiple Attribute Decision Making in the Manufacturing Environment -- 2. Improved Multiple Attribute Decision  Making Methods -- 3. Applications of Improved MADM Methods to the Decision Making Problems of Manufacturing Environment -- 4. A Novel Subjective and Objective Integrated Multiple Attribute Decision Making Method -- 5. A Novel Weighted Euclidean Distance Based Approach -- 6. A Combinatorial Mathematics Based Decision Making Method -- 7. Comparison of Different MADM Methods for Different Decision Making Situations of the Manufacturing Environment -- 8. Concluding Remarks.
In: Springer eBooksSummary: Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker’s subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples.  Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods  a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.
Tags from this library: No tags from this library for this title. Log in to add tags.
Star ratings
    Average rating: 0.0 (0 votes)
No physical items for this record

1. Multiple Attribute Decision Making in the Manufacturing Environment -- 2. Improved Multiple Attribute Decision  Making Methods -- 3. Applications of Improved MADM Methods to the Decision Making Problems of Manufacturing Environment -- 4. A Novel Subjective and Objective Integrated Multiple Attribute Decision Making Method -- 5. A Novel Weighted Euclidean Distance Based Approach -- 6. A Combinatorial Mathematics Based Decision Making Method -- 7. Comparison of Different MADM Methods for Different Decision Making Situations of the Manufacturing Environment -- 8. Concluding Remarks.

Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods presents the concepts and details of applications of MADM methods. A range of methods are covered including Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VIšekriterijumsko KOmpromisno Rangiranje (VIKOR), Data Envelopment Analysis (DEA), Preference Ranking METHod for Enrichment Evaluations (PROMETHEE), ELimination Et Choix Traduisant la Realité (ELECTRE), COmplex PRoportional ASsessment (COPRAS), Grey Relational Analysis (GRA), UTility Additive (UTA), and Ordered Weighted Averaging (OWA). The existing MADM methods are improved upon and three novel multiple attribute decision making methods for solving the decision making problems of the manufacturing environment are proposed. The concept of integrated weights is introduced in the proposed subjective and objective integrated weights (SOIW) method and the weighted Euclidean distance based approach (WEDBA) to consider both the decision maker’s subjective preferences as well as the distribution of the attributes data of the decision matrix. These methods, which use fuzzy logic to convert the qualitative attributes into the quantitative attributes, are supported by various real-world application examples.  Also, computer codes for AHP, TOPSIS, DEA, PROMETHEE, ELECTRE, COPRAS, and SOIW methods are included. This comprehensive coverage makes Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods  a key reference for the designers, manufacturing engineers, practitioners, managers, institutes involved in both design and manufacturing related projects. It is also an ideal study resource for applied research workers, academicians, and students in mechanical and industrial engineering.

There are no comments on this title.

to post a comment.