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A Multiple-Criteria Decision Sorting Model for Pharmaceutical Suppliers Classification Under Multiple Uncertainties

  • Renata PelissariEmail author
  • Sarah Ben-Amor
  • Maria Celia de Oliveira
Chapter
Part of the Lecture Notes in Logistics book series (LNLO)

Abstract

Selecting and evaluating suppliers is a major supply-chain concern for any company. It is even more crucial in pharmaceutical industries since delivering the right product to the right people at the right time requires specific conditions of storage and strict rules regarding expiry dates. In this context, supplier selection seems to be a complex task that involves a variety of conflicting criteria such as quality, performance history, guarantee policies, productive capacity, price and time. Therefore, many Multiple-criteria Decision Making (MCDM) methods have been applied to solve the supplier selection problem. However, most methods address only the ranking and choice problems. Besides, evaluating suppliers with regard to each criterion involves the presence of uncertainties and heterogeneous information, i.e., qualitative and quantitative data. The objective of this work is to propose a sorting MCDM model for pharmaceutical supplier selection under multiple uncertainties and heterogeneous information. The proposed model is based on an integration of the FlowSort and SMAA methods and Fuzzy theory. It allows pharmaceutical companies to develop a rating system to classify suppliers into categories, as actual and potential suppliers, in a context with multiple uncertainties and heterogeneous data information.

Notes

Acknowledgements

This research was supported by CAPES, the Brazilian Government Agency that supports Higher Education Personnel.

References

  1. Almeida-Dias, J., Figueira, J., & Roy, B. (2010). Electre Tri-C: A multiple criteria sorting method based on characteristic reference actions. European Journal of Operational Research, 204(3), 565–580.CrossRefGoogle Scholar
  2. Almeida-Dias, J., Figueira, J., & Roy, B. (2012). A multiple criteria sorting method where each category is characterized by several reference actions: The Electre Tri-nC method. European Journal of Operational Research, 217(3), 567–579.CrossRefGoogle Scholar
  3. American Hospital Association. AHA survey on drug shortages (2011).Google Scholar
  4. Araz, C. (2007). Multi-criteria based novel strategic sourcing methodologies. Ph.D. Thesis, Dokuz Eyll University.Google Scholar
  5. Araz, C., & Ozkarahan, I. (2007). Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure. International Journal of Production Economics, 106(2), 585–606.CrossRefGoogle Scholar
  6. Behzadian, M., Kazemzadeh, R., Albadvi, A., & Aghdasi, M. (2010). Promethee: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 200(1), 198–215.CrossRefGoogle Scholar
  7. Ben Amor, S., Martel, J. M., & Guitouni, A. (2015). A synthesis of information imperfection representations for decision aid. Information Systems and Operational Research, 53(2), 68–77.Google Scholar
  8. Brans, J., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The promethee method. European Journal of Operational Research, 24(2), 228–238.CrossRefGoogle Scholar
  9. Campos, A. C. S. M., Mareschal, B., & de Almeida, A. T. (2015). Fuzzy flow sort: An integration of the flowsort method and fuzzy set theory for decision making on the basis of inaccurate quantitative data. Information Sciences, 293, 115–124.CrossRefGoogle Scholar
  10. Canada Pharmacists Association. Canadian drug shortages survey (2010).Google Scholar
  11. Chai, J., Liu, J. N., & Ngai, E. W. (2013). Application of decision-making techniques in supplier selection: A systematic review of literature. Expert Systems with Applications, 40(10), 3872–3885.CrossRefGoogle Scholar
  12. Chen, S., & Hwang, C. (1992). Fuzzy multiple attribute decision making: Methods and applications (1st ed.). Berlin: Springer-Verlag.CrossRefGoogle Scholar
  13. Durbach, I. N., & Stewart, T. J. (2012). Modeling uncertainty in multi-criteria decision analysis. European Journal of Operational Research, 223(1), 1–14.CrossRefGoogle Scholar
  14. Ertay, T., Kahveci, T., & Tabanl, R. (2011). An integrated multi-criteria group decision-making approach to efficient supplier selection and clustering using fuzzy preference relations. International Journal of Computer Integrated Manufacturing, 24(12), 1152–1167.Google Scholar
  15. European Association of Hospital Pharmacists. Medicine shortages in European hospitals (2013).Google Scholar
  16. Figueira, J., De Smet, J., Mareschal, B., & Brans, J. (2004). MCDA methods for sorting and clustering problems: PROMETHEE TRI and PROMETHEE cluster. Technical Report TR/SMG/2004-002, Universit Libre de Bruxelles.Google Scholar
  17. Fox, E., Sweet, B., & Jensen, V. (2014). Drug shortages: A complex health care crisis. Mayo Clinic Proceedings, 89(3), 361–373.CrossRefGoogle Scholar
  18. Govindan, K., & Jepsen, M. B. (2016). ELECTRE: A comprehensive literature review on methodologies and applications. European Journal of Operational Research, 250(1), 1–29.CrossRefGoogle Scholar
  19. Govindan, K., & Jepsen, M. B. (2016). Supplier risk assessment based on trapezoidal intuitionistic fuzzy numbers and ELECTRE TRI-C: A case illustration involving service suppliers. Journal of the Operational Research Society, 67(2), 339–376.CrossRefGoogle Scholar
  20. Govindan, K., Rajendran, S., Sarkis, J., & Murugesan, P. (2015). Multi criteria decision making approaches for green supplier evaluation and selection: A literature review. Journal of Cleaner Production, 98, 66–83. Special Volume: Support your future today! Turn environmental challenges into opportunities.Google Scholar
  21. Guarnieri, P., & De Almeida, A. T. (2016). A multicriteria decision model for collaborative partnerships in supplier strategic management. Journal of Advanced Manufacturing Systems, 15(03), 101–131.CrossRefGoogle Scholar
  22. Janssen, P., & Nemery, P. (2013). An extension of the flowsort sorting method to deal with imprecision. 4OR, 11(2), 171–193.Google Scholar
  23. Kadziński, M., & Tervonen, T. (2013). Stochastic ordinal regression for multiple criteria sorting problems. Decision Support Systems, 55(1), 55–66.CrossRefGoogle Scholar
  24. Kim, P., Simoens, S., Casteels, M., & Huys, I. (2015). Insights into european drug shortages: A survey of hospital pharmacists. PLoS ONE, 10(3), 1–13.Google Scholar
  25. Lahdelma, R., Hokkanen, J., & Salminen, P. (1998). SMAA—Stochastic multiobjective acceptability analysis. European Journal of Operational Research, 106(1), 137–143.CrossRefGoogle Scholar
  26. Lahdelma, R., Miettinen, K., & Salminen, P. (2002). Stochastic multicriteria acceptability analysis using achievement functions. Turku Centre for Computer Science Technical Report Series, 459.Google Scholar
  27. Lahdelma, R., & Salminen, P. (2001). SMAA-2: Stochastic multicriteria acceptability analysis for group decision making. Operations Research, 49(3), 444–454.CrossRefGoogle Scholar
  28. Lahdelma, R., & Salminen, R. (2010). A method for ordinal classification in multicriteria decision making. In International Conference on Artificial Intelligence and Applications, pp. 420–425.Google Scholar
  29. Morrissey, J. (2012). The drug shortage. Hospitals & Health Networks, 86(1), 46–50.Google Scholar
  30. Nemery, P., Campos, A. C. S. M., Mareschal, B., & de Almeida, A. T. (2015). Addendum on: “Fuzzy FlowSort: An integration of the FlowSort method and fuzzy set theory for decision making on the basis of inaccurate quantitative data”. Information Sciences, 315(Supplement C), 54–55.Google Scholar
  31. Nemery, P., & Lamboray, C. (2008). Flow sort: A flow-based sorting method with limiting or central profiles. TOP, 16(1), 90–113.CrossRefGoogle Scholar
  32. Pelissari, R., Oliveira, M. C., Ben Amor, S., Abackerli, A. J. (2019). A new FlowSort-based method to deal with information imperfections in sorting decision-making problems. European Journal of Operational Research, 276(1), 235–246.Google Scholar
  33. R Development Core Team. (2008). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0.Google Scholar
  34. Roy, B. (1991). The outranking approach and the foundations of ELECTRE methods. Theory and Decision, 31, 49–73.CrossRefGoogle Scholar
  35. Saaty, T. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 24(6), 19–43.Google Scholar
  36. Schwartzberg, E., Ainbinder, D., Vishkauzan, A., & Gamzu, R. (2017). Drug shortages in Israel: Regulatory perspectives, challenges and solutions. Israel Journal of Health Policy Research, 6(1), 17.CrossRefGoogle Scholar
  37. Simi, D., Kovaevi, I., Svirevi, V., & Simi, S. (2017). 50 years of fuzzy set theory and models for supplier assessment and selection: A literature review. Journal of Applied Logic, 24, 85–96. SI:SOCO14.Google Scholar
  38. Tervonen, T., Figueira, J. R. J., Lahdelma, R., Dias, J. A. J., & Salminen, P. (2009). A stochastic method for robustness analysis in sorting problems. European Journal of Operational Research, 192(1), 236–242.CrossRefGoogle Scholar
  39. Tervonen, T., & Lahdelma, R. (2007). Implementing stochastic multicriteria acceptability analysis. European Journal of Operational Research, 178(2), 500–513.CrossRefGoogle Scholar
  40. The Multi-Stakeholder Steering Committee on Drug Shortages in Canada. (2017). Preventing Drug Shortages: Identifying Risks and Strategies to Address Manufacturing-Related Drug Shortages in Canada.Google Scholar
  41. Ventola, C. (2011). The drug shortage crisis in the United States: Causes, impact, and management strategies. Pharmacy and Therapeutics, 36(11), 740–757.PubMedPubMedCentralGoogle Scholar
  42. Vetschera, R. (2017). Deriving rankings from incomplete preference information: A comparison of different approaches. European Journal of Operational Research, 258(1), 244–253.CrossRefGoogle Scholar
  43. Weber, C. A., Current, J. R., & Benton, W. (1991). Vendor selection criteria and methods. European Journal of Operational Research, 50(1), 2–18.CrossRefGoogle Scholar
  44. Yu, W. (1992). ELECTRE TRI: Aspects mthodologiques et manuel d’utilisation. Document du LAMSADE 74, Universit-Paris-Dauphine.Google Scholar
  45. Zopounidis, C., & Doumpos, M. (1999). A multicriteria decision aid methodology for sorting decision problems: The case of financial distress. Computational Economics, 14(3), 197–218.CrossRefGoogle Scholar
  46. Zopounidis, C., & Doumpos, M. (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research, 138, 229–246.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Renata Pelissari
    • 1
    • 2
    Email author
  • Sarah Ben-Amor
    • 2
  • Maria Celia de Oliveira
    • 1
    • 3
  1. 1.Post Graduate Program of Industrial EngineeringMethodist University of PiracicabaSanta Bárbara d’OesteBrazil
  2. 2.Telfer Management SchoolUniversity of OttawaOttawaCanada
  3. 3.Engineering SchoolMackenzie Presbyterian UniversitySão PauloBrazil

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