Skip to main content

Using Differential Evolution to Develop a Carbon-Integrated Model for Performance Evaluation and Selection of Sustainable Suppliers in Indian Automobile Supply Chain

  • Conference paper
  • First Online:
Proceedings of Fifth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 437))

Abstract

Automobile industries worldwide are unified in opinion, that successful management of sustainable supply chains is the most important driver to improve both their economic and ecological performances. The significance of sustainable supply chain management (SSCM) is a critical corporate matter in the automobile industries that offers incredible potential for achieving better environmental performance, consumer fulfillment, pull down operating expenditures, reducing inventory investments in addition to achieving better fixed asset usage. The environment concerns, climatic changes, and additional ecological concerns in automobile industries are not only articulated by campaigners or researchers, but also by the common man as well, which has motivated the industries to focus on sustainability. The present research focuses on a DEA-based mathematical model and employs differential evolution to select the competent suppliers providing the utmost fulfillment for the sustainable criteria determined. This study aims to examine the sustainable supplier evaluation and selection practices likely to be adopted by the Indian automobile industry for their products.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jayal, A.D., Badurdeen, F., Dillon, Jr., O.W., Jawahir, I.S.: Sustainable manufacturing: Modeling and optimization challenges at the product, process and system levels. CIRP J. Manufact. Sci. Technol. 2(3), 144–152 (2010)

    Article  Google Scholar 

  2. Floridi, M., Pagni, S., Falorni, S., Luzzati, T.: An exercise in composite indicators construction: Assessing the sustainability of Italian regions. Ecol. Econ. 70(8), 1440–1447 (2011)

    Article  Google Scholar 

  3. Luthe, T., Schuckert, M.: Socially responsible investing–implications for leveraging sustainable development. In: Trends and Issues in Global Tourism 2011 (pp. 315–321). Springer Berlin Heidelberg (2011)

    Google Scholar 

  4. Paoletti, M.G., Gomiero, T., Pimentel, D.: Introduction to the special issue: towards a more sustainable agriculture. Crit. Rev. Plant Sci. 30(1–2), 2–5 (2011)

    Article  Google Scholar 

  5. Büyüközkan, G., Çifçi, G.: A novel fuzzy multi-criteria decision framework for sustainable supplier selection with incomplete information. Comput. Ind. 62(2), 164–174 (2011)

    Article  Google Scholar 

  6. Genovese, A., Koh, S.L., Bruno, G., Bruno, P.: Green supplier selection: a literature review and a critical perspective. In: 8th International Conference on Supply Chain Management and Information Systems (SCMIS), 2010 pp. 1–6. IEEE, Oct 2010

    Google Scholar 

  7. Purdy, L., Safayeni, F.: Strategies for supplier evaluation: a framework for potential advantages and limitations. IEEE Trans. Eng. Manage. 47(4), 435–443 (2000)

    Article  Google Scholar 

  8. Storn, R., Price, K.: Differential evolution-a simple and efficient adaptive scheme for global optimization over continuous spaces. Berkeley: ICSI, CA, Technical Report TR-95-012 (1995)

    Google Scholar 

  9. Plagianakos, V.P., Tasoulis, D.K., Vrahatis, M.N.: A review of major application areas of differential evolution. In: Advances in Differential Evolution, pp. 197–238. Springer, Berlin Heidelberg (2008)

    Google Scholar 

  10. Wang, F., Jang, H.J.: Parameter estimation of a bioreaction model by hybrid differential evolution. In: Proceedings of the 2000 Congress on Evolutionary Computation, 2000, vol. 1, pp. 410–417. IEEE (2000)

    Google Scholar 

  11. Joshi, R., Sanderson, A.C.: Minimal representation multisensor fusion using differential evolution. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 29(1), 63–76 (1999)

    Article  Google Scholar 

  12. Ilonen, J., Kamarainen, J.K., Lampinen, J.: Differential evolution training algorithm for feed-forward neural networks. Neural Process. Lett. 17(1), 93–105 (2003)

    Article  Google Scholar 

  13. Ali, M., Siarry, P., Pant, M.: An efficient differential evolution based algorithm for solving multi-objective optimization problems. Eur. J. Oper. Res. 217(2), 404–416 (2012)

    MathSciNet  MATH  Google Scholar 

  14. Jauhar, S., Pant, M., Deep, A.: Differential evolution for supplier selection problem: a DEA based approach. In: Proceedings of the Third International Conference on Soft Computing for Problem Solving, pp. 343–353. Springer India, Jan 2014

    Google Scholar 

  15. Parker, P.: Environmental initiatives among japanese automakers: new technology, EMS, recycling and lifecycle approaches. Environ.: J. interdiscip. Stud. 29(3) (2001)

    Google Scholar 

  16. Kearney, A.T.: Building world class supply chain in India, Conference on Auto Supply Chain Management, 2013. www.atkearney.com. Accessed 23 Nov 2014

  17. SIAM India—Society of Indian Automobile Manufacturers (SIAM). www.siamindia.com.Accessed. Accessed 18 Jan 2014

  18. Bhattacharya, S., Mukhopadhyay, D., Giri, S.: Supply chain management in indian automotive industry: complexities, challenges and way ahead. Int. J. Managing Value Supply Chains 5(2) (2014)

    Google Scholar 

  19. Nieuwenhuis, P., Wells, P.: The Automotive Industry and The Environment: A Technical, Business and Social Future, Woodhead, Cambridge. 2003, Elsevier (2003)

    Google Scholar 

  20. Agarwal, P., Sahai, M., Mishra, V., Bag, M., Singh, V.: A review of multi-criteria decision making techniques for supplier evaluation and selection. Int. J. Ind. Eng. Comput. 2(4), 801–810 (2011)

    Google Scholar 

  21. Weber, C.A., Current, J.R., Benton, W.C.: Vendor selection criteria and methods. Eur. J. Oper. Res. 50(1), 2–18 (1991)

    Article  Google Scholar 

  22. Degraeve, Z., Labro, E., Roodhooft, F.: An evaluation of vendor selection models from a total cost of ownership perspective. Eur. J. Oper. Res. 125(1), 34–58 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  23. Jauha, S.K., Pant, M.: Recent trends in supply chain management: a soft computing approach. In: Proceedings of Seventh International Conference on Bio-Inspired Computing: Theories and Applications (BIC-TA 2012), pp. 465–478. Springer India, Jan 2013

    Google Scholar 

  24. De Boer, L., Labro, E., Morlacchi, P.: A review of methods supporting supplier selection. Eur. J. Purchasing Supply Manage. 7(2), 75–89 (2001)

    Article  Google Scholar 

  25. Holt, G.D.: Which contractor selection methodology? Int. J. Project Manage. 16(3), 153–164 (1998)

    Article  MathSciNet  Google Scholar 

  26. Aamer, A.M., Sawhney, R.: Review of suppliers selection from a production perspective. In: Proceedings of the IIE Annual Conference and Exhibition, pp. 2135–2140 (2004)

    Google Scholar 

  27. Ho, W., Xu, X., Dey, P.K.: Multi-criteria decision making approaches for supplier evaluation and selection: A literature review. Eur. J. Oper. Res. 202(1), 16–24 (2010)

    Article  MATH  Google Scholar 

  28. Tahriri, F., Osman, M.R., Ali, A., Yusuff, R.M.: A review of supplier selection methods in manufacturing industries. Suranaree J. Sci. Technol. 15(3), 201–208 (2008)

    Google Scholar 

  29. Jauhar, S.K., Pant, M.: Genetic algorithms, a nature-inspired tool: review of applications in supply chain management. In: Proceedings of Fourth International Conference on Soft Computing for Problem Solving, pp. 71–86. Springer India, Jan 2015

    Google Scholar 

  30. Cheraghi, S.H., Dadashzadeh, M., Subramanian, M.: Critical success factors for supplier selection: an update. J. Appl. Bus. Res. (JABR) 20(2) (2011)

    Google Scholar 

  31. Noci, G.: Designing ‘green’vendor rating systems for the assessment of a supplier’s environmental performance. Eur. J. Purchasing Supply Manage. 3(2), 103–114 (1997)

    Article  Google Scholar 

  32. Zhu, Q., Geng, Y.: Integrating environmental issues into supplier selection and management. Greener Manage. Int. 2001(35), 26–40 (2001)

    Article  Google Scholar 

  33. Jauhar, S.K., Pant, M., Deep, A.: An approach to solve multi-criteria supplier selection while considering environmental aspects using differential evolution. In: Swarm, Evolutionary, and Memetic Computing, pp. 199–208. Springer International Publishing (2013)

    Google Scholar 

  34. Lai, Y.F.: Green supplier evaluation in green supply chain management—examples of printed circuit board suppliers. Unpublished Master’s Thesis, Department of Resource Engineering, National Cheng-Kung University, Taiwan (in Chinese) (2004)

    Google Scholar 

  35. Seuring, S., Müller, M.: Core issues in sustainable supply chain management—a Delphi study. Bus. Strategy Environ. 17(8), 455–466 (2008)

    Article  Google Scholar 

  36. Awasthi, A., Chauhan, S.S., Goyal, S.K.: A fuzzy multicriteria approach for evaluating environmental performance of suppliers. Int. J. Prod. Econ. 126(2), 370–378 (2010)

    Article  Google Scholar 

  37. Jauhar, S.K., Pant, M., Abraham, A.: A novel approach for sustainable supplier selection using differential evolution: a case on pulp and paper industry. In: Intelligent Data analysis and its Applications, vol. II, pp. 105–117. Springer International Publishing (2014)

    Google Scholar 

  38. Buyukozkan, G., Çifci, G.: A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers. Expert Syst. Appl. 39, 3000–3011 (2012)

    Article  Google Scholar 

  39. Kannan, D., Khodaverdi, R., Olfat, L., Jafarian, A., Diabat, A.: Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. J. Clean. Prod. 47, 355–367 (2013)

    Article  Google Scholar 

  40. Falatoonitoosi, E., Ahmed, S., Sorooshian, S.: A multicriteria framework to evaluate supplier’s greenness. In: Abstract and Applied Analysis, vol. 2014. Hindawi Publishing Corporation, March 2014

    Google Scholar 

  41. Yazdani, M.: An integrated MCDM approach to green supplier selection. Int. J. Ind. Eng. Comput. 5(3), 443–458 (2014)

    Google Scholar 

  42. Jalhar, S.K., Pant, M., Nagar, M.C.: Differential evolution for sustainable supplier selection in pulp and paper industry: a DEA based approach. Comput. Methods Mater. Sci. 15 (2015)

    Google Scholar 

  43. Simpson, D.F., Power, D.J.: Use the supply relationship to develop lean and green suppliers. Int. J. Supply chain manage. 10(1), 60–68 (2005)

    Article  Google Scholar 

  44. Lee, S.Y., Klassen, R.D.: Drivers and Enablers That Foster Environmental Management Capabilities in Small-and Medium-Sized Suppliers in Supply Chains. Prod. Oper. Manage. 17(6), 573–586 (2008)

    Article  Google Scholar 

  45. Weele, A.J.: Purchasing and Supply Chain Management. Cengage Learning EMEA, Andover, UK (2010)

    Google Scholar 

  46. Scannell, T.V., Vickery, S.K., Droge, C.L.: (2000). Upstream supply chain management and competitive performance in the automotive supply industry. J. Bus. Logistics 21(1)

    Google Scholar 

  47. Awaysheh, A., Klassen, R.D.: The impact of supply chain structure on the use of supplier socially responsible practices. Int. J. Oper. Prod. Manage. 30(12), 1246–1268 (2010)

    Article  Google Scholar 

  48. Geffen, C.A., Rothenberg, S.: Suppliers and environmental innovation: the automotive paint process. Int. J. Oper. Prod. Manage. 20(2), 166–186 (2000)

    Article  Google Scholar 

  49. Klassen, R.D., Vachon, S.: Collaboration and evaluation in the supply chain: the impact on plant-level environmental investment. Prod. Oper. Manage. 12(3), 336–352 (2003)

    Article  Google Scholar 

  50. Despotis, D.K., Stamati, L.V., Smirlis, Y.G.: Data envelopment analysis with nonlinear virtual inputs and outputs. Eur. J. Oper. Res. 202(2), 604–613 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  51. Ramanathan, R. (ed.): A Tool for Performance Measurement. Sage Publication Ltd., New Delhi (2003)

    Google Scholar 

  52. Wen, U.P., Chi, J.M.: Developing green supplier selection procedure: a DEA approach. In: 17th International Conference on Industrial Engineering and Engineering Management (IE&EM), 2010 IEEE, pp. 70, 74, 29–31 Oct 2010. doi:10.1109/ICIEEM.2010.5646615

  53. Dobos, I., Vörösmarty, G.: Supplier selection and evaluation decision considering environmental aspects. sz. Mőhelytanulmány, HU ISSN 1786–3031, Oct 2012

    Google Scholar 

  54. Kumar, P., Mogha, S.K., Pant, M.: Differential evolution for data envelopment analysis. In: Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) Dec 20–22, 2011, pp. 311–319, Springer India, Jan 2012

    Google Scholar 

  55. Srinivas, T.: Data envelopment analysis: models and extensions. In: Production/Operation Management Decision Line, pp. 8–11 (2000)

    Google Scholar 

  56. Charnes, A., Cooper, W.W., Rhodes, E.: Measuring the efficiency of decision making units. Eur. J. Oper. Res. 2(6), 429–444 (1978)

    Google Scholar 

  57. Banker, R.D., Charnes, A., Cooper, W.W.: Some models for estimating technical and scale inefficiencies in data envelopment analysis. Manage. Sci. 30(9), 1078–1092 (1984)

    Google Scholar 

  58. Rogalsky, T., Derksen, R.W., Kocabiyik, S.: Differential evolution in aerodynamic optimization. In: Proceedings of 46th Annual Conference, Canadian Aeronautics Space Institute, pp. 29–36 (1999)

    Google Scholar 

  59. Joshi, R., Sanderson, A.C.: Minimal representation multi-sensor fusion using differential evolution. IEEE Trans. Syst. Man Cybernetics. Part A 29, 63–76 (1999)

    Google Scholar 

  60. Ray, T., Kang, T., Chye, S.K.: An evolutionary algorithm for constrained optimization. In: Whitley, D., Goldberg, D., Cantu-Paz, E., Spector, L., Parmee, I., Beyer, H.G. (eds.) Proceeding of the Genetic and Evolutionary Computation Conference (GECCO 2000), pp. 771–777 (2000)

    Google Scholar 

  61. Shirouyehzad, H., Lotfi, F.H., Dabestani, R.: A data envelopment analysis approach based on the service qualtiy concept for vendor selection. In: International Conference on Computers & Industrial Engineering, 2009. CIE 2009, pp. 426–430. IEEE, July 2009

    Google Scholar 

  62. http://www.london2012.com/documents/locog-publications/locog-guidelines-on-carbon-emissions-of-products-and-services.pdf. Accessed 12 Oct 2013

  63. Cooper, W.W., Seiford, L.M., Tone, K.: Data envelopment analysis: a comprehensive text with models, applications, references and DEA-Solver Software. Second editions. Springer (2007). ISBN: 387452818, 490

    Google Scholar 

  64. Ansari, I.A, Pant, M., Neri, F.: Analysis of gray scale watermark in RGB host using SVD and PSO. In: IEEE Computational Intelligence for Multimedia, Signal and Vision Processing (CIMSIVP), pp. 1–7 (2014)

    Google Scholar 

  65. Zaheer, H., Pant, M., Kumar, S., Monakhov, O., Monakhova, E., Deep, K.: A new guiding force strategy for differential evolution. Int. J. Syst. Assur. Eng. Manag. 1–14 (2015), doi:10.1007/s13198-014-0322-6

    Google Scholar 

  66. Ansari, I.A., Pant, A., Ahn, C.W.: SVD based fragile watermarking scheme for tamper localization and self-recovery. Int. J. Mach. Learn. Cyber. 1–15 (2015), doi:10.1007/s13042-015-0455-1

    Google Scholar 

  67. Zaheer, H., Pant, M.: A differential evolution approach for solving integer programming problems. In: Proceedings of Fourth International Conference on Soft Computing for Problem Solving, pp. 413–424. Springer India (2015)

    Google Scholar 

  68. Ansari, I.A., Pant, A., Ahn, C.W.: Robust and false positive free watermarking in IWT domain using SVD and ABC. Eng. Appl. Artif. Intell. 49, 114–125 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Sunil Kumar Jauhar .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media Singapore

About this paper

Cite this paper

Jauhar, S.K., Pant, M. (2016). Using Differential Evolution to Develop a Carbon-Integrated Model for Performance Evaluation and Selection of Sustainable Suppliers in Indian Automobile Supply Chain. In: Pant, M., Deep, K., Bansal, J., Nagar, A., Das, K. (eds) Proceedings of Fifth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 437. Springer, Singapore. https://doi.org/10.1007/978-981-10-0451-3_47

Download citation

  • DOI: https://doi.org/10.1007/978-981-10-0451-3_47

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-0450-6

  • Online ISBN: 978-981-10-0451-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics