Advertisement

Soft Computing

, Volume 23, Issue 24, pp 13215–13233 | Cite as

A decision support system for single-period single sourcing problem in supply chain management

  • Alireza EydiEmail author
  • Leyla Fazli
Methodologies and Application
  • 82 Downloads

Abstract

A basic part of the logistic management of organizations is purchasing function, and appropriate supplier selection is one of the main responsibilities of this function. Appropriate supplier selection has an important role in reducing costs, increasing competitiveness and the share of market as well as improving customers’ satisfaction. Hence, the use of accurate and efficient techniques for supplier selection problems is out of question. Due to the importance of appropriate supplier selection, lots of research have been focused on this topic, but only a few of them considered the supplier selection problem with the process of reducing the set of all suppliers to a smaller set of eligible suppliers. Therefore, in this paper, based on data envelopment analysis models, a new hybrid methodology is presented for evaluating potential suppliers and selecting the best supplier (single sourcing) under certainty environment for a single-period by applying the strategy of reducing the number of potential suppliers. This methodology includes two phases: (1) classifying suppliers into efficient and inefficient suppliers, and hence reducing the set of all suppliers into a smaller set of eligible suppliers, and (2) evaluating the efficient (eligible) suppliers. Finally, a sample problem is demonstrated to examine the proposed methodology in comparison with traditional methods.

Keywords

Supplier selection Single sourcing Pre-qualification of potential suppliers Single-period Data envelopment analysis models 

Notes

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animal

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

Informed consent was obtained from all individual participants included in the study.

References

  1. Adila A (2001) Predictors of university academic performance in Colombia instituto colombiano de neuropsicologia, Bogota, Colombia. Int J Educ Res 35:411–417CrossRefGoogle Scholar
  2. Aissaoui N, Haouari M, Hassini E (2007) Supplier selection and order lot sizing modeling: a review. Comput Oper Res 34:3516–3540zbMATHCrossRefGoogle Scholar
  3. Alirezaei M-R, Rafiei Sani M-R (2010) Development on AHP/DEA method for ranking decision-making units. Iran J Ind Manag 5:83–102 (In Persian) Google Scholar
  4. Awasthi A, Govindan K, Gold S (2017) Multi-tier sustainable global supplier selection using a fuzzy AHP-VIKOR based approach. Int J Prod Econ 195:106–117CrossRefGoogle Scholar
  5. Azadi M, Jafarian M, Farzipoor Saen R, Mirhedayatian S-M (2015) A new fuzzy DEA model for evaluation of efficiency and effectiveness of suppliers in sustainable supply chain management context. Comput Oper Res 54:274–285MathSciNetzbMATHCrossRefGoogle Scholar
  6. Bagherzadeh A, Dori B (2010) ANP application for selecting the best supplier in supply chain. Iran J Humanit Teach Manag Res Iran 4:1–21 (In Persian) Google Scholar
  7. Beuthe M, Scannella G (2001) Comparative analysis of UTA multicriteria methods. Eur J Oper Res 130(2):246–262zbMATHCrossRefGoogle Scholar
  8. Bottani E, Rizzi A (2008) An adapted multi-criteria approach to suppliers and products selection—an application oriented to lead-time reduction‖. Int J Prod Econ 111(2):763–781CrossRefGoogle Scholar
  9. Chamodrakas I, Batis D, Martakos D (2010) Supplier selection in electronic market places using satisficing and fuzzy AHP. Expert Syst Appl 37:490–498CrossRefGoogle Scholar
  10. Charnes A, Cooper W-W, Rohdes E (1978) Measuring the efficiency of decision making units. Eur J Oper Res 2(6):429–444MathSciNetzbMATHCrossRefGoogle Scholar
  11. Che Z-H, Chang Y-F (2016) Integrated methodology for supplier selection: the case of a sphygmomanometer manufacturer in Taiwan. J Bus Econ Manag 17(1):17–34CrossRefGoogle Scholar
  12. Chen Y-Q, Lu H, Lu W, Zhang N (2010) Analysis of project delivery systems in Chinese construction industry with data envelopment analysis (DEA). Eng Constr Archit Manag 17(6):598–614CrossRefGoogle Scholar
  13. Choi T-M (2013) Optimal apparel supplier selection with forecast updates under carbon emission taxation scheme. Comput Oper Res 40:2646–2655MathSciNetzbMATHCrossRefGoogle Scholar
  14. De Boer L, Labro E, Morlacchi P (2001) A review of methods supporting supplier selection. Eur J Purch Supply Manag 7:75–84CrossRefGoogle Scholar
  15. Degraeve Z, Labro E, Roodhooft F (2000) An evaluation of vendor selection models from a total cost of ownership perspective. Eur J Oper Res 125(1):34–58zbMATHCrossRefGoogle Scholar
  16. Dobos I, Vörösmarty G (2014) Green supplier selection and evaluation using DEA-type composite indicators. Int J Prod Econ 157:273–278CrossRefGoogle Scholar
  17. Emel A-B, Oral M, Reisman A, Yolalan R (2003) A credit rating approach for the commercial banking sector. J Socio-Econ Plan Sci 37(2):103–123CrossRefGoogle Scholar
  18. Eydi A, Bakhtiari M (2017) A multi-product model for evaluating and selecting two layers of suppliers considering environmental factors. Rairo-Oper Res 51:875–902MathSciNetzbMATHCrossRefGoogle Scholar
  19. Fallahpour A-R, Amindoust A, Antuchevičienė J, Yazdani M (2017) Nonlinear genetic-based model for supplier selection: a comparative study. Technol Econ Dev Econ 23(1):178–195CrossRefGoogle Scholar
  20. Ferreira L, Borenstein D (2012) A fuzzy-bayesian model for supplier selection. Expert Syst Appl 39:7834–7844CrossRefGoogle Scholar
  21. Ghobadian A, Stainer A, Kiss T (1993) A computerized vendor rating system. In: Proceeding of the first international symposium on logistics. The University of Nottingham, Nottingham, UK, pp 321–328Google Scholar
  22. Ghodsypour S-H, O’Brien C (1998) A decision support system for supplier selection using on integrated analytic hierarchy process and linear programing. Int J Prod Econ 56–57:199–212CrossRefGoogle Scholar
  23. Govindan K, Kadziński M, Sivakumar R (2017) Application of a novel PROMETHEE-based method for construction of a group compromise ranking to prioritization of green suppliers in food supply chain. Omega 71:129–145CrossRefGoogle Scholar
  24. Ho W, Xu X, Dey P-K (2010) Multi-criteria decision making approaches for supplier evaluation and selection: a literature review. Eur J Oper Res 202(1):16–24zbMATHCrossRefGoogle Scholar
  25. Hosseini S-M, Barker K (2016) A Bayesian network model for resilience-based supplier selection. Int J Prod Econ 180:68–87CrossRefGoogle Scholar
  26. Jacquet-Lagrèze E, Siskos Y (1982) Assessing a set of additive utility functions for multicriteria decision making: the UTA method. Eur J Oper Res 10(2):151–164zbMATHCrossRefGoogle Scholar
  27. Jain V, Kumar S, Kumar A, Chandra C (2016) An integrated buyer initiated decision-making process for green supplier selection. J Manuf Syst 41:256–265CrossRefGoogle Scholar
  28. Jauhar S-K, Pant M (2017) Integrating DEA with DE and MODE for sustainable supplier selection. J Comput Sci 21:299–306CrossRefGoogle Scholar
  29. Kannan D (2018) Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. Int J Prod Econ 195:391–418CrossRefGoogle Scholar
  30. Khataei M, Haji Yousefi Abad R (2008) Technical efficiency evaluation of Housing Bank using data envelopment analysis (DEA). Iran J Plan Budg 103:55–84 (In Persian) Google Scholar
  31. Kumar R, Padhi S-S, Sarkar A (2018) Supplier selection of an Indian heavy locomotive manufacturer: an integrated approach using Taguchi loss function, TOPSIS, and AHP. IIMB Manag Rev (in press) Google Scholar
  32. Liou J-J-H, Chuang Y-T (2010) Developing a hybrid multi-criteria model for selection of outsourcing providers. Expert Syst Appl 37:3755–3761CrossRefGoogle Scholar
  33. Liu P, Zhang X (2011) Research on the supplier selection of a supply chain based on entropy weight and improved ELECTRE-III method. Int J Prod Res 49(3):637–646CrossRefGoogle Scholar
  34. Luthra S, Govindan K, Kannan D, Mangla S-K, Garg C-P (2017) An integrated framework for sustainable supplier selection and evaluation in supply chains. J Clean Prod 140(3):1686–1698CrossRefGoogle Scholar
  35. Michaels R, Kumar A, Samu S (1995) Activity—specific role stress in purchasing. Int J Purch Mater Manag 31(1):11–19Google Scholar
  36. Monczka R, Trent R, Handfield R (1998) Purchasing and supply chain management. Western College Publishing, CincinnatiGoogle Scholar
  37. Nguyen H-T, Dawal S-Z-M, NukmanY Aoyama H (2014) A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes. Expert Syst Appl 41(6):3078–3090CrossRefGoogle Scholar
  38. Park S-C, Lee J-H (2017) Supplier selection and stepwise benchmarking: a new hybrid model using DEA and AHP based on cluster analysis. J Oper Res Soc 69(2):1–20Google Scholar
  39. Pastor J-T (1996) Translation invariance in data envelopment analysis: a generalization. Ann Oper Res 66:93–102MathSciNetzbMATHCrossRefGoogle Scholar
  40. Patton W-E (1997) Individual and joint decision making in industrial vendor selection. J Bus Res 38(2):115–122CrossRefGoogle Scholar
  41. Pavić Z, Novoselac V (2013) Notes on TOPSIS method. Int J Res Eng Sci 1(2):5–12Google Scholar
  42. Petroni A, Braglia M (2000) Vendor selection using principal component analysis. J Supply Chain Manag Glob Rev Purch Supply 36:9–63Google Scholar
  43. Premachandra I-M (2001) A note on DEA vs. Principal component analysis: an improvement to Joe Zhu’s approach. Eur J Oper Res 132:553–560MathSciNetzbMATHCrossRefGoogle Scholar
  44. Qin J, Liu X, Pedrycz W (2017a) A multiple attribute interval type-2 fuzzy group decision making and its application to supplier selection with extended LINMAP method. Soft Comput 21(12):3207–3226zbMATHCrossRefGoogle Scholar
  45. Qin J, Liu X, Pedrycz W (2017b) An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment. Eur J Oper Res 258(2):626–638MathSciNetzbMATHCrossRefGoogle Scholar
  46. Qiu J, Wang T, Yin S, Gao H (2017a) Data-based optimal control for networked double-layer industrial processes. IEEE Trans Industr Electron 64(5):4179–4186CrossRefGoogle Scholar
  47. Qiu J, Wei Y, Wu L (2017b) A novel approach to reliable control of piecewise affine systems with actuator faults. IEEE Trans Circuits Syst II Express Briefs 64(8):957–961CrossRefGoogle Scholar
  48. Qiu J, Wei Y, Karimi H-R, Gao H (2018) Reliable control of discrete-time piecewise-affine time-delay system via output feedback. IEEE Trans Reliab 67(1):79–91CrossRefGoogle Scholar
  49. Rajabi Asadabadi M (2017) A customer based supplier selection process that combines quality function deployment, the analytic network process and a markov chain. Eur J Oper Res 263(3):1049–1062zbMATHCrossRefGoogle Scholar
  50. Razmi J, Rabani M, Rezaei K, Karbasian S (2004) Providing a decision making support model for suppliers planning, evaluation and selection. Iran J Faculty Eng Tehran Univ 5:693–708Google Scholar
  51. Rezaei J, Fahim P-B-M, Tavasszy L (2014) Supplier selection in the airline retail industry using a funnel methodology: conjunctive screening method and fuzzy AHP. Expert Syst Appl 41(18):8165–8179CrossRefGoogle Scholar
  52. Rezaei J, Nispeling T, Sarkis J, Tavasszy L (2016) A supplier selection life cycle approach integrating traditional and environmental criteria using the Best Worst Method. J Clean Prod 135:577–588CrossRefGoogle Scholar
  53. Sarkar S, Pratihar D-K, Sarkar B (2018) An integrated fuzzy multiple criteria supplier selection approach and its application in a welding company. J Manuf Syst 46:163–178CrossRefGoogle Scholar
  54. Shabani A, Visani F, Barbieri P, Dullaert W, Vigo D (2018) Reliable estimation of suppliersʼ total cost of ownership: an imprecise data envelopment analysis model with common weights. Omega (in press) Google Scholar
  55. Shabanpour H, Yousefi S, Farzipoor Saen R (2017a) Forecasting efficiency of green suppliers by dynamic data envelopment analysis and artificial neural networks. J Clean Prod 142(2):1098–1107CrossRefGoogle Scholar
  56. Shabanpour H, Yousefi S, Farzipoor Saen R (2017b) Future planning for benchmarking and ranking sustainable suppliers using goal programming and robust double frontiers DEA. Transp Res Part D 50:29–143CrossRefGoogle Scholar
  57. Simić D, Svirčević V, Simić S (2015) A hybrid evolutionary model for supplier assessment and selection in inbound logistics. J Appl Logic 13(2):138–147zbMATHCrossRefGoogle Scholar
  58. Sinuany-Stern Z, Mehrez A, Hadad Y (2000) An AHP/DEA methodology for ranking decision making units. Int Transp Oper Res 7:109–124MathSciNetCrossRefGoogle Scholar
  59. Siskos Y, Yannacopoulos D (1985) UTASTAR: an ordinal regression method for building additive value functions. Invest Oper 5(1):39–53Google Scholar
  60. Sueyoshi T (2001) Theory and methodology extended DEA—discriminant analysis. Eur J Oper Res 131:324–351zbMATHCrossRefGoogle Scholar
  61. Sueyoshi T (2006) DEA-discriminant analysis: methodological comparison among eight discriminant analysis approaches. Eur J Oper Res 169:247–272MathSciNetzbMATHCrossRefGoogle Scholar
  62. Sueyoshi T, Goto M (2013) A use of DEA-DA to measure importance of R&D expenditure in Japanese information technology industry. Decis Support Syst 54:941–952CrossRefGoogle Scholar
  63. Tavana M, Fallahpour A-R, Di Caprio D, Santos-Arteaga F-J (2016) A hybrid intelligent fuzzy predictive model with simulation for supplier evaluation and selection. Expert Syst Appl 61:129–144CrossRefGoogle Scholar
  64. Theiben S, Spinler S (2014) Strategic analysis of manufacturer–supplier partnerships: an ANP model for collaborative CO2 reduction management. Eur J Oper Res 233:383–397CrossRefGoogle Scholar
  65. Tofallis C (1997) Input efficiency profiling: an application to airlines. Comput Oper Res 24(3):253–258zbMATHCrossRefGoogle Scholar
  66. Valipour Parkouhi S, Safaei Ghadikolaei A (2017) A resilience approach for supplier selection: using fuzzy analytic network process and grey VIKOR techniques. J Clean Prod 161:431–451CrossRefGoogle Scholar
  67. Wan S-P, Xu G-L, Dong J-Y (2017) Supplier selection using ANP and ELECTRE II in interval 2-tuple linguistic environment. Inf Sci 385–386:19–38CrossRefGoogle Scholar
  68. Wang M, Qiu J, Chadli M, Wang M (2016) A switched system approach to exponential stabilization of sampled-data T–S fuzzy systems with packet dropouts. IEEE Trans Cybern 46(12):3145–3156CrossRefGoogle Scholar
  69. Weber C-A, Current J-R, Benton W-C (1991) Vendor selection criteria and methods. Eur J Oper Res 50(1):2–18zbMATHCrossRefGoogle Scholar
  70. Wu C, Barnes D (2011) A literature review of decision-making models and approaches for partner selection in agile supply chains. J Purch Supply Manag 17:256–274CrossRefGoogle Scholar
  71. Wu Y, Chen K, Zeng B, Xu H, Yang Y (2016) Supplier selection in nuclear power industry with extended VIKOR method under linguistic information. Appl Soft Comput 48:444–457CrossRefGoogle Scholar
  72. Yazdani M, Chatterjee P, Zavadskas E-K, Hashemkhani Zolfani S (2017) Integrated QFD-MCDM framework for green supplier selection. J Clean Prod 142(4):3728–3740CrossRefGoogle Scholar
  73. Zhu J (1998) Data envelopment analysis vs. principal component analysis: an illustrative study of economic performance of Chinese cities. Eur J Oper Res 111:50–61zbMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of EngineeringUniversity of KurdistanSanandajIran
  2. 2.Department of Industrial EngineeringFerdowsi University of MashhadMashhadIran

Personalised recommendations