Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods, 2013 Volume 2 Springer Series in Advanced Manufacturing Series

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.

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.

Dr. R. Venkata Rao is a Professor in the Department of Mechanical Engineering, S.V. National Institute of Technology, Surat, India. His institute is directly under the financial and administrative control of the Government of India. He has 21 years of teaching and research experience. He was deputed by the Government of India to Asian Institute of Technology, Bangkok, Thailand as a visiting Professor in 2008 and 2010. He gained his B.Tech in 1988, M.Tech in 1991, and Ph.D. in 2002. Dr. Rao's research interests include: CAD/CAM, CIMS, advanced optimization techniques, and fuzzy multiple attribute decision making methods. He has published more than 250 research papers in national and international journals and conference proceedings and received national and international awards for best research work. He has been a reviewer to many national and international journals and on the editorial boards of few International journals.

He has already authored three books entitled “Decision Making in the Manufacturing Environment Using Graph Theory and Fuzzy Multiple Attribute Decision Making Methods” and “Advanced Modeling and Optimization of Manufacturing Processes: International Research and development” and “Mechanical Design Optimization Using Advanced Optimization Techniques” and all these books have been published by Springer Verlag, UK in 2007, 2011 and 2012 respectively.

Demonstrates how various fuzzy multiple attribute decision making methods such as AHP, GRA, OWA, UTA, DEA, PROMETHEE, COPRAS, WEDBA, CBMA, and SOIW methods can be effectively used for decision making in various situations of the manufacturing environment

Presents decision making methodologies in a logical, simple manner so that they can be conveniently implemented in the real manufacturing environment

Documents the latest research works including the author’s own works related to each of the listed topics

Includes algorithms and computer codes for various MADM methods

Includes supplementary material: sn.pub/extras