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Modeling and Optimization of Strategic Sustainable Sourcing

  • Krishnendu MukherjeeEmail author
Chapter
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Part of the Studies in Systems, Decision and Control book series (SSDC, volume 88)

Abstract

Nowadays, sustainable development has received lot of attention from academic as well as from practitioners. Different industries already implemented strategies for sustainable development as it improves cooperation among companies along the supply chain to give better flow of capital, material, and information. In brief, sustainable development gives better supply chain visibility to prevent future risk or uncertainty. In this chapter, three different methods are discussed with example and case study. A two-stage sustainable supplier selection method is proposed first for multi-product assembly-to-order (ATO) production system to deal with demand uncertainty, green house gas (GHG) emission, reliability of supply, level of disassembly, and social issues of supplier selection. It is an integrated approach of intuitionistic fuzzy AHP (IF-AHP) and multi-objective genetic algorithm (MOGA). Second, a cascaded fuzzy inference system is discussed with an example. A decision support system is developed in this regard with Microsoft Visual Basic.NET (VB.NET) and MATLAB. Finally, strategic sustainable sourcing is discussed for a large number of suppliers with a case study. In the last method, “R” software and spreadsheet are used for K-means data clustering technique. In brief, an attempt has been made in this chapter to discuss several methods from sustainable sourcing to strategic sustainable procurement process.

Keywords

ATO Intuitionistic fuzzy AHP IF-AHP MOGA Sustainable supplier selection Cascaded fuzzy inference system MATLAB VB.NET Strategic sustainable sourcing K-means data clustering 

References

  1. Amindoust A, Ahmed S, Saghafinia A, Bahreininejad A (2012) Sustainable supplier selection: A ranking model based on fuzzy inference system. Appl Soft Comput 12:1668–1677CrossRefGoogle Scholar
  2. Bai C, Sarkis J (2010) Green supplier development: Analytical evaluation using rough set theory. J Clean Prod. doi: 10.1016/j.jclepro.2010.01.016 Google Scholar
  3. Brink S, Diehl JC, Stevels A (1998) ECO-QUEST, an ecodesign self audit tool for suppliers of the electronics industry. In: Proc. the 1998 international symposium on electronics and the environment, May 4–6, Oak Brook, Illinois, pp 129–132Google Scholar
  4. Carr AS, Pearson JN (1999) Strategically managed buyer–seller relationships and performance outcomes. J Oper Manag 17:497–519CrossRefGoogle Scholar
  5. Charrad M, Ghazzali N, Boiteau V, Niknafs A (2014) NbClust: An R package for determining the relevant number of clusters in a data set. J Stat Softw 61(6):1–36CrossRefGoogle Scholar
  6. Chen TY (2011) A comparative analysis of score functions for multiple criteria decision making in intuitionistic fuzzy settings. Inf Sci 181:3652–3676CrossRefGoogle Scholar
  7. Das SK, Mathew S (1999) Characterization of material outputs from an electronics demanufacturing facility. In: proc. IEEE international symposium on electronics and the environment, Boston, MA, May 11–13, pp 251–256Google Scholar
  8. Das SK, Naik S (2002) Process planning for product disassembly. Int J Prod Res 40(6):1335–1355CrossRefGoogle Scholar
  9. Das S, Yedlarajiah D (2002) An integer programming model for prescribing material recovery strategies. In: Proc. IEEE international symposium on electronics and the environment, May 6–9, pp 118–122Google Scholar
  10. De Toni A, Nassimbeni G (1999) Buyer–supplier operational practices, sourcing policies and plant performance: result of an empirical research. Int J Prod Res 37(3):597–619CrossRefzbMATHGoogle Scholar
  11. Franke J (1995) Political evolution of EMAS: perspectives from the EU, National governments and industrial groups. Bus Strategy Environ 5(3):14–17Google Scholar
  12. Franklin Associates (1991) Product life-cycle assessment: guidelines and principles. EPA Report, #68-CO-0003Google Scholar
  13. Ghodsypour SH, O’Brien C (1998) A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming. Int J Prod Econ 56–57:199–212CrossRefGoogle Scholar
  14. Guan Z, Jin Z, Zou B (2007) A Multi-Objective Mixed-Integer Stochastic Programming Model for the Vendor Selection Problem under Multi-Product Purchases. Inform Management Sci 18(3):241–252MathSciNetzbMATHGoogle Scholar
  15. Gungor A, Gupta SM (1999) Issues in environmentally conscious manufacturing and product recovery: A survey. Comput Ind Eng 36:811–853CrossRefGoogle Scholar
  16. Gupta M (1995) Environmental management and its impact on the operations function. Int J Oper Prod Manage 15(8):34–51CrossRefGoogle Scholar
  17. Handfield R, Walton S, Sroufe R, Melnyk S (2002) Applying environmental criteria to supplier assessment: a study in the application of the analytical hierarchy process. Eur J Oper Res 141:70–87CrossRefzbMATHGoogle Scholar
  18. Hsu C-W, Hu AH (2009) Applying hazardous substance management to supplier selection using analytic network process. J Clean Prod 17:255–264CrossRefGoogle Scholar
  19. Hunt R, Sellers J, Franklin W (1992) Resource and environmental profile analysis: a life cycle environmental assessment for products and procedures. Environ Impact Assess Rev 12(3):245–269CrossRefGoogle Scholar
  20. Ishii K, Eubanks CF, Marco PD (1994) Design for product retirement and material life-cycle. Mater Des 15(4):225–233CrossRefGoogle Scholar
  21. Kim K, Song I, Kim J, Jeong B (2006) Supply planning model for remanufacturing system in reverse logistics environment. Comput Ind Eng 51:279–287CrossRefGoogle Scholar
  22. Kotha S (1995) Mass customisation: implementing the emerging paradigm for competitive advantage. Strategic Manage J 16:21–42CrossRefGoogle Scholar
  23. Lee HI, Kang HY, Hsu CF, Hung HC (2009) A green supplier selection model for high-tech industry. Expert Syst Appl 36(4):7917–7927CrossRefGoogle Scholar
  24. Levan LS (1998) Life cycle assessment: measuring environmental impact. www.fpl.fs.fed.us/documnts/pdf1998/levan98b.pdf
  25. Milligan GW, Cooper MC (1985) An examination of procedures for determining the number of clusters in a data set. Psychometrika 50(2):159–179CrossRefGoogle Scholar
  26. Mukherjee K, Sarkar B, Bhattacharya A (2011) Comments on the erratum to “Supply planning model for remanufacturing system in reverse logistics environment” [Comput. Ind. Eng. 51 (2006) 279–287]. Comput Ind Eng 61:1349–1350CrossRefGoogle Scholar
  27. Muralidharan C, Anantharaman N, Deshmukh (2002) A multi-criteria group decision making model for supplier rating. J Supply Chain Manage Fall 22–33Google Scholar
  28. News letter of life cycle assessment society of Japan (JLCA), edition 1. www.jemai.or.jp
  29. Noci G (1997) Design “green” vendor rating systems for the assessment of a supplier’s environmental performance. Eur J Purchasing Supply Manage 3(2):103–114CrossRefGoogle Scholar
  30. Pine BJ (1993) Mass customisation. HBS Press, BostonGoogle Scholar
  31. Sanchez PP, Soyer R (1998) Information concepts and pair-wise comparison matrices. Inf Processing Lett 68:185–188CrossRefzbMATHGoogle Scholar
  32. Shin H, Collier DA, Wilson DD (2000) Supply management orientation and supplier buyer performance. J Oper Manage 18:317–333CrossRefGoogle Scholar
  33. Smith KG, Carroll SJ, Ashford SJ (1995) Intra-and inter-organizational cooperation: toward a research agenda. Acad Manag J 38(1):7–23CrossRefGoogle Scholar
  34. Spekman RE (1988) Perceptions of strategic vulnerability among industrial buyers and its effect on information search and supplier evaluation. J Bus Res 17:313–326CrossRefGoogle Scholar
  35. Stilwell JR, Canty PK, Montrone A (1991) Packaging for the environment. American Management Association, New YorkGoogle Scholar
  36. Svoboda S (1995) Note on life cycle analysis www.umich.edu/~nppcpub/resources/compendia/CORPpdfs/CORPlca.pdf
  37. Szmidt E, Kacprzyk J (2000) Distance between intuitionistic fuzzy sets. Fuzzy Sets, Syst 114(3):505–518MathSciNetCrossRefzbMATHGoogle Scholar
  38. Tracey M, Tan CL (2001) Empirical analysis of supplier selection and involvement, customer satisfaction and firm performance. Supply Chain Manage: Int J 6(4):174–188CrossRefGoogle Scholar
  39. Van Hoek RI (1999) From reversed logistics to green supply chains. Supply Chain Manage: Int J 4(3):129–135CrossRefGoogle Scholar
  40. Wang M, Perkins JR (2006) Using interval alignment policies for efficient production control of supply chain systems. Int J Ind Syst Eng 1(1–2):87–108Google Scholar
  41. Wang M, Perkins JR (2011) Time interval alignment (ia) policies, boundary and applications with multiple stream arrivals. J Syst Sci Syst Eng 20(4):400–415CrossRefGoogle Scholar
  42. Wu CH, Kuo TC, Lu YY (2007) Environmental principles applicable to green supplier evaluation by using multi-objective decision analysis. Int J Prod Res 45(18–19):4317–4331zbMATHGoogle Scholar
  43. Xia W, Wu Z (2007) Supplier selection with multiple criteria in volume discount environments. Omega 35:494–504CrossRefGoogle Scholar
  44. Zeid I, Gupta SM (2002) Computational algorithm to evaluate product disassembly cost index. In: Proc. of the SPIE international conference on environmentally conscious manufacturing II, February 11, pp 23–31Google Scholar
  45. Zhang HC, Li J, Shrivastava P, Whitely A, Eugene M (2004) A web-based system for reverse manufacturing and product environmental impact assessment considering end-of-life dispositions. CIRP Annals-Manuf Technol 53(1):5–8CrossRefGoogle Scholar

Copyright information

© Springer (India) Pvt. Ltd. 2017

Authors and Affiliations

  1. 1.Mechanical EngineeringUniversity of Engineering and ManagementJaipurIndia

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