Advanced Operations Management for Complex Systems Analysis: Introduction

Part of the SpringerBriefs in Applied Sciences and Technology book series (BRIEFSAPPLSCIENCES)


This chapter has had a brief overview of multi-criteria decision making methods for operations management, especially for complex decision-making and complex system analysis, and the main content of each chapter has been introduced: a two-stage interval best-worst method based on the multiplicative constraint was developed in Chap.  2, 2-tupe DEMATEL (decision making trial and evaluation laboratory) was introduced in Chap.  3, fuzzy best-worst network method combined with ISM was proposed for analyzing the complex systems was illustrated in Chap.  4, and a multi-stakeholder intuitionistic fuzzy multi-criteria decision making method was presented in Chap.  5. Typical problems about complex decision-making and complex system analysis were investigated to show the applicability of these advanced operations management methods.


  1. H. Aboutorab, M. Saberi, M.R. Asadabadi, O. Hussain, E. Chang, ZBWM: the Z-number extension of best worst method and its application for supplier development. Expert Syst. Appl. 107, 115–125 (2018)CrossRefGoogle Scholar
  2. L. Abdullah, N. Zulkifli, Integration of fuzzy AHP and interval type-2 fuzzy DEMATEL: an application to human resource management. Expert Syst. Appl. 42(9), 4397–4409 (2015)CrossRefGoogle Scholar
  3. F. Abadi, I. Sahebi, A. Arab, A. Alavi, H. Karachi, Application of best-worst method in evaluation of medical tourism development strategy. Decis. Sci. Lett. 7(1), 77–86 (2018)CrossRefGoogle Scholar
  4. M.A. Agi, R. Nishant, Understanding influential factors on implementing green supply chain management practices: an interpretive structural modelling analysis. J. Environ. Manage. 188, 351–363 (2017)CrossRefGoogle Scholar
  5. H. Alidrisi, Prioritizing critical success factors for six sigma implementation using interpretive structural modeling. Am. J. Ind. Bus. Manage. 4(12), 697 (2014)Google Scholar
  6. R. Attri, N. Dev, V. Sharma, Interpretive structural modelling (ISM) approach: an overview. Res. J. Manage. Sci. 2(2), 3–8 (2013)Google Scholar
  7. J.P. Brans, Y. De Smet, PROMETHEE methods, in Multiple Criteria Decision Analysis (Springer, New York, 2016), pp. 187–219Google Scholar
  8. D.Y. Chang, Applications of the extent analysis method on fuzzy AHP. Eur. J. Oper. Res. 95(3), 649–655 (1996)CrossRefGoogle Scholar
  9. B.R. Debata, K. Sree, B. Patnaik, S.S. Mahapatra, Evaluating medical tourism enablers with interpretive structural modeling. Benchmarking: Int. J. 20(6), 716–743 (2013)Google Scholar
  10. T. Entani, K. Sugihara, Uncertainty index based interval assignment by interval AHP. Eur. J. Oper. Res. 219(2), 379–385 (2012)CrossRefGoogle Scholar
  11. J.R. Figueira, S. Greco, B. Roy, R. Słowiński, An overview of ELECTRE methods and their recent extensions. J. Multi-Criteria Decis. Anal. 20(1–2), 61–85 (2013)CrossRefGoogle Scholar
  12. E.H. Forman, S.I. Gass, The analytic hierarchy process—an exposition. Oper. Res. 49(4), 469–486 (2001)CrossRefGoogle Scholar
  13. A. Gabus, E. Fontela, World problems, an invitation to further thought within the framework of DEMATEL (1972)Google Scholar
  14. A. Gabus, E. Fontela, Perceptions of the world problematique: communication procedure, communicating with those bearing collective responsibility (1973)Google Scholar
  15. S. Guo, H. Zhao, Fuzzy best-worst multi-criteria decision-making method and its applications. Knowl.-Based Syst. 121, 23–31 (2017)CrossRefGoogle Scholar
  16. H. Gupta, Evaluating service quality of airline industry using hybrid best worst method and VIKOR. J. Air Transp. Manage. 68, 35–47 (2018)CrossRefGoogle Scholar
  17. M. Keshavarz Ghorabaee, E.K. Zavadskas, Z. Turskis, J. Antucheviciene, A new combinative distance-based assessment (CODAS) method for multi-criteria decision-making. Econ. Comput. Econ. Cybern. Stud. Res. 50(3) (2016)Google Scholar
  18. Y. Kuo, T. Yang, G.W. Huang, The use of grey relational analysis in solving multiple attribute decision-making problems. Comput. Ind. Eng. 55(1), 80–93 (2008)CrossRefGoogle Scholar
  19. I. Linkov, F.K. Satterstrom, G. Kiker, C. Batchelor, T. Bridges, E. Ferguson, From comparative risk assessment to multi-criteria decision analysis and adaptive management: recent developments and applications. Environ. Int. 32(8), 1072–1093 (2006)CrossRefGoogle Scholar
  20. A. Mandal, S.G. Deshmukh, Vendor selection using interpretive structural modelling (ISM). Int. J. Oper. Prod. Manag. (1994)Google Scholar
  21. G.A. Mendoza, H. Martins, Multi-criteria decision analysis in natural resource management: a critical review of methods and new modelling paradigms. For. Ecol. Manage. 230(1–3), 1–22 (2006)CrossRefGoogle Scholar
  22. Q. Mou, Z. Xu, H. Liao, An intuitionistic fuzzy multiplicative best-worst method for multi-criteria group decision making. Inf. Sci. 374, 224–239 (2016)CrossRefGoogle Scholar
  23. B. Öztaysi, S.Ç. Onar, E. Boltürk, C. Kahraman, Hesitant fuzzy analytic hierarchy process, in 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (IEEE, 2015), pp. 1–7Google Scholar
  24. J. Ren, A. Manzardo, S. Toniolo, A. Scipioni, Sustainability of hydrogen supply chain. Part I: Identification of critical criteria and cause–effect analysis for enhancing the sustainability using DEMATEL. Int. J. Hydrogen Energy 38(33), 14159–14171 (2013)Google Scholar
  25. J. Ren, H. Liang, Measuring the sustainability of marine fuels: a fuzzy group multi-criteria decision making approach. Transp. Res. Part D: Transp. Environ. 54, 12–29 (2017)CrossRefGoogle Scholar
  26. J. Ren, H. Liang, F.T. Chan, Urban sewage sludge, sustainability, and transition for Eco-City: multi-criteria sustainability assessment of technologies based on best-worst method. Technol. Forecast. Soc. Chang. 116, 29–39 (2017)CrossRefGoogle Scholar
  27. J. Ren, X. Ren, L. Dong, A. Manzardo, C. He, M. Pan, Multiactor multicriteria decision making for life cycle sustainability assessment under uncertainties. AIChE J. 64(6), 2103–2112 (2018)CrossRefGoogle Scholar
  28. J. Rezaei, Best-worst multi-criteria decision-making method. Omega 53, 49–57 (2015)CrossRefGoogle Scholar
  29. J. Rezaei, T. Nispeling, J. Sarkis, L. Tavasszy, A supplier selection life cycle approach integrating traditional and environmental criteria using the best worst method. J. Clean. Prod. 135, 577–588 (2016)CrossRefGoogle Scholar
  30. J. Rezaei, J. Wang, L. Tavasszy, Linking supplier development to supplier segmentation using best worst method. Expert Syst. Appl. 42(23), 9152–9164 (2015)CrossRefGoogle Scholar
  31. J. Rezaei, Best-worst multi-criteria decision-making method: some properties and a linear model. Omega 64, 126–130 (2016)CrossRefGoogle Scholar
  32. T.L. Saaty, Decision making with the analytic hierarchy process. Int. J. Serv. Sci. 1(1), 83–98 (2008)Google Scholar
  33. S. Sahoo, A. Dhar, A. Kar, Environmental vulnerability assessment using grey analytic hierarchy process based model. Environ. Impact Assess. Rev. 56, 145–154 (2016)CrossRefGoogle Scholar
  34. A. Sanayei, S.F. Mousavi, A. Yazdankhah, Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Syst. Appl. 37(1), 24–30 (2010)CrossRefGoogle Scholar
  35. H.S. Shih, H.J. Shyur, E.S. Lee, An extension of TOPSIS for group decision making. Math. Comput. Model. 45(7–8), 801–813 (2007)CrossRefGoogle Scholar
  36. R.K. Singh, S.K. Garg, S.G. Deshmukh, Interpretive structural modelling of factors for improving competitiveness of SMEs. Int. J. Prod. Qual. Manage. 2(4), 423–440 (2007)Google Scholar
  37. J. Thakkar, S.G. Deshmukh, A.D. Gupta, R. Shankar, Selection of third-party logistics (3PL): a hybrid approach using interpretive structural modeling (ISM) and analytic network process (ANP). Supply Chain Forum: Int. J. 6(1), 32–46 (2005)CrossRefGoogle Scholar
  38. G. van de Kaa, L. Kamp, J. Rezaei, Selection of biomass thermochemical conversion technology in the Netherlands: a best worst method approach. J. Clean. Prod. 166, 32–39 (2017)CrossRefGoogle Scholar
  39. C. Vasanthakumar, S. Vinodh, K. Ramesh, Application of interpretive structural modelling for analysis of factors influencing lean remanufacturing practices. Int. J. Prod. Res. 54(24), 7439–7452 (2016)CrossRefGoogle Scholar
  40. G.H. Tzeng, J.J. Huang, Multiple Attribute Decision Making: Methods and Applications (Chapman and Hall/CRC, 2011)Google Scholar
  41. Z. Wang, J. Ren, M.E. Goodsite, G. Xu, Waste-to-energy, municipal solid waste treatment, and best available technology: comprehensive evaluation by an interval-valued fuzzy multi-criteria decision making method. J. Clean. Prod. 172, 887–899 (2018)CrossRefGoogle Scholar
  42. W.W. Wu, Y.T. Lee, Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Syst. Appl. 32(2), 499–507 (2007)CrossRefGoogle Scholar
  43. X. Xia, K. Govindan, Q. Zhu, Analyzing internal barriers for automotive parts remanufacturers in China using grey-DEMATEL approach. J. Clean. Prod. 87, 811–825 (2015)CrossRefGoogle Scholar

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© The Author(s), under exclusive license to Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Industrial and Systems EngineeringHong Kong Polytechnic UniversityHong Kong SARChina

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