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Supplier Selection: An MCDA-Based Approach 1st ed. 2017 [Kietas viršelis]

  • Formatas: Hardback, 128 pages, aukštis x plotis: 235x155 mm, weight: 3495 g, 43 Illustrations, black and white; XX, 128 p. 43 illus., 1 Hardback
  • Serija: Studies in Systems, Decision and Control 88
  • Išleidimo metai: 13-Apr-2017
  • Leidėjas: Springer, India, Private Ltd
  • ISBN-10: 813223698X
  • ISBN-13: 9788132236986
Kitos knygos pagal šią temą:
Supplier Selection: An MCDA-Based Approach 1st ed. 2017Didesnis paveikslėlis
  • Formatas: Hardback, 128 pages, aukštis x plotis: 235x155 mm, weight: 3495 g, 43 Illustrations, black and white; XX, 128 p. 43 illus., 1 Hardback
  • Serija: Studies in Systems, Decision and Control 88
  • Išleidimo metai: 13-Apr-2017
  • Leidėjas: Springer, India, Private Ltd
  • ISBN-10: 813223698X
  • ISBN-13: 9788132236986
Kitos knygos pagal šią temą:
Pastovi nuoroda: https://www.kriso.lt/db/9788132236986.html
Raktažodžiai:

The purpose of this book is to present a comprehensive review of the latest research and development trends at the international level for modeling and optimization of the supplier selection process for different industrial sectors. It is targeted to serve two audiences: the MBA and PhD student interested in procurement, and the practitioner who wishes to gain a deeper understanding of procurement analysis with multi-criteria based decision tools to avoid upstream risks to get better supply chain visibility. The book is expected to serve as a ready reference for supplier selection criteria and various multi-criteria based supplier’s evaluation methods for forward, reverse and mass customized supply chain. This book encompasses several criteria, methods for supplier selection in a systematic way based on extensive literature review from 1998 to 2012. It provides several case studies and some useful links which can serve as a starting point for interested researchers. In the appendix several computer code written in MatLab and VB.NET is also included for the interested reader. Lucid explosion of various techniques used to select and evaluate suppliers is one of the unique characteristic of this book. Moreover, this book gives in depth analysis of selection and evaluation of suppliers for traditional supply chain, closed loop supply chain, supply chain for customized product, green supply chain, sustainable supply chain and also depicts methods for supply base reduction and selection of large number of suppliers.

1 Overview
1(30)
1.1 Introduction
1(2)
1.2 Characteristics and Classification of Criteria
3(1)
1.3 Classification of Decision Problem
4(1)
1.4 MCDA
4(13)
1.4.1 Analytic Hierarchy Process (AHP)
5(1)
1.4.2 Types of Scale
6(1)
1.4.3 Prioritization Methods---EM or LLSM---Which One Is Better?
7(1)
1.4.4 Rank Reversal in AHP
7(2)
1.4.5 Validation of AHP
9(1)
1.4.6 Different Forms of AHP
10(1)
1.4.7 Application of AHP
11(1)
1.4.8 Analytic Network Process (ANP)
12(1)
1.4.9 Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)
13(1)
1.4.10 Fuzzy Hierarchical TOPSIS
14(1)
1.4.11 Rank Reversal Problem in TOPSIS
15(1)
1.4.12 TOPSIS and Other Methods
15(1)
1.4.13 Application of TOPSIS
16(1)
1.4.14 VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje; in Serbian)
17(1)
1.5 Uncertainty Analysis with MCDA
17(9)
1.5.1 Fuzzy Set---An Introduction
18(2)
1.5.2 Cascaded Fuzzy Inference System
20(2)
1.5.3 Intuitionistic Fuzzy Set (IFS)---An Introduction
22(2)
1.5.4 Dealing Uncertainty with AHP
24(1)
1.5.5 Dealing Uncertainty with TOPSIS
24(1)
1.5.6 Dealing Uncertainty with VIKOR
24(1)
1.5.7 Fuzzy AHP by Hand Calculation
24(2)
1.6 Conclusion
26(5)
References
27(4)
2 Modeling and Optimization of Traditional Supplier Selection
31(28)
2.1 Introduction
31(1)
2.2 State-of-the-Art Literature Review of Supplier Selection Methods
32(3)
2.3 Pareto Analysis of Supplier Selection Criteria
35(3)
2.4 Stages of Procurement
38(3)
2.5 Qualities of Good Supplier
41(1)
2.6 How to Prepare Supply Base?
42(1)
2.7 Supplier Selection for Mass Customized System
42(1)
2.8 Hybrid Methods for Supplier Selection
43(11)
2.8.1 Modified Extent Fuzzy AHP and GA (MEFAHP-GA)
43(2)
2.8.2 Fuzzy TOPSIS-MOGA
45(1)
2.8.3 Multi-Objective Model for Supplier Selection
46(2)
2.8.4 Case Study
48(6)
2.9 Conclusion
54(5)
References
54(5)
3 Mass Customization
59(8)
3.1 Introduction
59(1)
3.2 Constraints of Mass Customization
60(1)
3.3 Postponement
61(1)
3.4 Sourcing Postponement---A New Kind of Postponement Strategy
61(1)
3.5 Advantages of Postponement Strategy
62(1)
3.6 Drivers of Postponement Strategy
63(1)
3.7 Customer Order Decoupling Point (CODP)
64(1)
3.8 Conclusion
65(2)
References
66(1)
4 Modeling and Optimization of Strategic Sustainable Sourcing
67(34)
4.1 Introduction
67(1)
4.2 Literature Review
68(5)
4.2.1 Viability of Dickson's 23 Criteria for Green Supply Chain
73(1)
4.3 Economical Aspects of Reverse Supply Chain
73(2)
4.3.1 Disassembly Cost
74(1)
4.3.2 Recycling Profit
75(1)
4.3.3 Optimum Level of Disassembly
75(1)
4.4 Sustainable Mass Customized System
75(2)
4.4.1 Stages and Enablers of Sustainable Mass Customized System
76(1)
4.4.2 Sourcing Strategies for Sustainable Mass Customized System
76(1)
4.5 Mathematical Model for SPS
77(4)
4.6 Decision Support System for Strategic Sustainable Sourcing in Volume Discount Environment
81(10)
4.7 Strategic Sourcing of Large Number of Suppliers: An Illustrative Case
91(6)
4.7.1 Case Study
92(5)
4.8 Conclusion
97(4)
References
97(4)
5 A Note on Limitations of FAHP
101(12)
5.1 Introduction
101(2)
5.2 Other Limitations of Fuzzy AHP Models
103(1)
5.3 Consistency Index and Optimization Methods for AHP
103(3)
5.3.1 Weighted Least Square Method (Chu et al. 1979)
104(1)
5.3.2 Error Minimization Method (Chen and Triantaphyllou 2001)
104(2)
5.3.3 Logarithmic Least Square Method
106(1)
5.3.4 Goal Programming Method (Bryson 1995)
106(1)
5.4 Alternative Approaches to FAHP
106(4)
5.4.1 Method of Triantaphyllou and Lin (1996)
107(1)
5.4.2 Least Square Distance Method (Wang and Parkan 2006; with Kind Permission from Elsevier Limited)
107(1)
5.4.3 Defuzzification-Based Least Square Method (Wang and Parkan 2006; with Kind Permission from Elsevier Limited)
108(1)
5.4.4 Preference Programming (Salo and Hamalainen 1995)
108(1)
5.4.5 Fuzzy Preference Programming (Mikhailov and Singh 2003)
109(1)
5.5 Conclusion
110(3)
References
111(2)
Appendix: MCDA Tools and Meta-Heuristic Techniques: Sample Codes 113
Krishnendu Mukherjee is an operations research scientist with the Operations Research Machine Learning & Analytics Experts (ORMAE), where he has been dealing with several projects for multi-national companies in India and abroad. He did his Bachelor of Engineering in Mechanical from Jadavpur University and Master of Engineering from BITS Pilani. He also worked as invited reviewer of IJPE, EJOR, JORS, IJAHP etc. In 2004, he got opportunity to design and develop innovative carpet backing machine at IICT, Bhadohi, as one of the core team member. In 2014, he received US copy right for developing computer code to facilitate selection and evaluation of n-number of suppliers in fuzzy environment. In 2015, he introduced new concept of postponement strategy to prevent upstream supply chain risk. He has published 15 papers in international journals/conferences. His areas of research include multi-criteria decision analysis, fuzzy set theory, mixed integer programming, linear programming, constrained programming, non-linear programming, optimization, supply chain management, sustainability, procurement analysis, vehicle routing, airlines scheduling, tankers scheduling etc. He has also completed his PhD work including the preparation of final draft of PhD thesis at Jadavpur University. This book encompasses extended work of his PhD thesis. He previously worked with National Institute of Technology Silchar (former REC); Ministry of Manpower, Oman; Indian Institute of Carpet Technology, Ministry of Textile, Govt. of India; Heritage Institute of Technology, Kolkata; MAHE, Dubai etc.