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An improved PROMETHEE II method based on Axiomatic Fuzzy Sets

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Abstract

This paper proposes an improved Preference Ranking Organization Method for Enrichment Evaluations II method based on Axiomatic Fuzzy Sets (AFS). With AFS, the preference functions of alternatives can be easily decided by the ranking and difference degrees of performance values on each attribute. Furthermore, the method considers the objective weights of importance of the attributes as well as the subjective preferences of the decision maker to decide the integrated weights of importance of the attributes. In case study, the evaluation of the industrial economic benefit of 16 provinces or municipalities of China is used to demonstrate the performance of the proposed method. The ranking results show that the whole evaluating procedure is feasible and effective.

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References

  1. Koele P (1995) Multiple attribute decision making: an introduction. Sage Publications, Thousand Oaks

    Google Scholar 

  2. Hwang CL, Yoon K (1981) Multiple attribute decision making: methods and applications. Springer, New York

    Book  MATH  Google Scholar 

  3. Peng Y, Kou G, Wang G, Shi Y (2011) FAMCDM: a fusion approach mcdm methods to rank multiclass classification algorithms. Omega Int J Manag 39:677–689

    Article  Google Scholar 

  4. Georgopoulou E, Sarafidis Y, Diakoulaki D (1998) Design and implementation of a group DSS for sustaining renewable energies exploitation. Eur J Oper Res 109:483–500

    Article  MATH  Google Scholar 

  5. Behzadian M, Kazemzadeh RB, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on methodologies and applications. Eur J Oper Res 200:198–215

    Article  MATH  Google Scholar 

  6. Rao RV, Patel BK (2010) Decision making in the manufacturing environment using an improved PROMETHEE method. Int J Prod Res 48(16):4665–4682

    Article  MATH  Google Scholar 

  7. Anand G, Kodali R (2008) Selection of lean manufacturing systems using the PROMETHEE. J Model Manag 3(1):40–70

    Article  Google Scholar 

  8. Roozbahani A, Zahraie B, Tabesh M (2012) PROMETHEE with precedence order in the criteria (PPOC) as a new group decision making aid: an application in urban water supply management. Water Resour Manag 26:3581–3599

    Article  Google Scholar 

  9. Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184(1):255–265

    Article  MATH  Google Scholar 

  10. Albadvi A, Chaharsooghi SK, Esfahanipour A (2007) Decision making in stock trading: an application of PROMETHEE. Eur J Oper Res 177:673–683

    Article  MATH  Google Scholar 

  11. Baourakis G, Doumpos M, Kalogeras N, Zopounidis C (2002) Multicriteria analysis and assessment of financial viability of agribusinesses: the case of marketing co-operatives and juice-producing companies. Agribusiness 18(4):543–558

    Article  Google Scholar 

  12. Mavrotas G, Diakoulaki D, Caloghirou Y (2006) Project prioritization under policy restrictions: a combination of MCDA with 0–1 programming. Eur J Oper Res 171:296–308

    Article  MATH  MathSciNet  Google Scholar 

  13. Elevli B, Demirci A (2004) Multicriteria choice of ore transport system for an underground mine: application of PROMETHEE methods. J South Afr Inst Min Metall 104(5):251–256

    Google Scholar 

  14. Liu PD, Guan ZL (2009)  Evaluation research on the quality of the railway passenger service based on the linguistic variables and the improved PROMETHEE-II method. J Comput  4(3):265–270

  15. Fernndez-Castro AS, Jimnez M (2005) PROMETHEE: an extension through fuzzy mathematical programming. J Oper Res Soc 56:119–122

    Article  Google Scholar 

  16. Parreiras RO, Vasconcelos JA (2007) A multiplicative version of PROMETHEE II applied to multiobjective optimization problems. Eur J Oper Res 183:729–740

    Article  MATH  Google Scholar 

  17. Lim MCH, Ayoko GA, Morawska L, Ristovski ZD, Jayaratne ER (2007) Influence of fuel composition on polycyclic aromatic hydrocarbon emissions from a fleet of in-service passenger cars. Atmos Environ 41:150–160

    Article  Google Scholar 

  18. Brans JP, Vincke P (1985) A preference ranking organisation method: the PROMETHEE method for MCDM. Manag Sci 31(6):647–656

    Article  MATH  MathSciNet  Google Scholar 

  19. Brans JP, Vincke P, Mareschal B (1986) How to select and how to rank projects: the PROMETHEE method. Eur J Oper Res 24(2):228–238

    Article  MATH  MathSciNet  Google Scholar 

  20. Brans JP, Mareschal B (2005) PROMETHEE methods in multiple criteria decision analysis: state of the art surveys. Chapter 5:163–195

    Google Scholar 

  21. Brans JP, Mareschal B (1994) The PROMCALC and GAIA decision support system for MCDA. Decis Support Syst 12(4–5):297–310

    Article  Google Scholar 

  22. Wang JJ, Yang DL (2007) Using a hybrid multi-criteria decision aid method for information systems outsourcing. Comput Oper Res 34(12):3691–3700

    Article  MATH  Google Scholar 

  23. Hyde K, Maier H, Colby C (2003) Incorporating uncertainty in the PROMETHEE MCDA method. J Multi Criteria Decis Anal 12:245–259

    Article  Google Scholar 

  24. Salminen P, Hokkanen J, Lahdelma R (1998) Comparing multicriteria methods in the context of environmental problems. Eur J Oper Res 104:485–496

    Article  MATH  Google Scholar 

  25. Podvezko V, Podviezko A (2010) Dependence of multi-criteria evaluation result on choice of preference functions and their parameters. Technol Econ Dev Econ 16(1):143–158

    Article  Google Scholar 

  26. Ma J, Fan ZP, Huang LH (1999) A subjective and objective integrated approach to determine attribute weights. Eur J Oper Res 112:397–404

    Article  MATH  Google Scholar 

  27. Chen TY, Li CH (2010) Determining objective weights with intuitionistic fuzzy entropy measures: a comparative analysis. Inf Sci 180:4207–4222

    Article  Google Scholar 

  28. Huang YS, Fang W, Chen SH (2010) Assessment on operational risk of power grid enterprises based on entropy weight and improved grey relation analysis, 2010 Second International Workshop on Education Technology and Computer Science, 448–451

  29. Huang JW (2008) Combining entropy weight and TOPSIS method for information system selection, In Proceedings of the IEEE conference on cybernetics and intelligent systems, 1281–1284

  30. Lo YF, Wen MH (2010) A fuzzy-AHP based technique for the decision of design feature selection in massively multiplayer online role-playing game development. Expert Syst Appl 37:8685–8693

    Article  Google Scholar 

  31. Chang DY (1996) Applications of the extent analysis method on fuzzy AHP. Eur J Oper Res 95:649–655

    Article  MATH  Google Scholar 

  32. Celik M, Er ID, Ozok AF (2009) Application of fuzzy extended AHP methodology on shipping registry selection: the case of Turkish maritime industry. Expert Syst Appl 36:190–198

    Article  Google Scholar 

  33. Wang Y, Jung KA, Yeo GT, Chou Ch (2014) Selecting a cruise port of call location using the fuzzy-AHP method: a case study in East Asia. Tour Manag 42:262–270

    Article  Google Scholar 

  34. Liu XD (1998) The fuzzy theory based on AFS algebras and AFS structure. J Math Anal Appl 217:459–478

    Article  MATH  MathSciNet  Google Scholar 

  35. Liu XD (1998) The fuzzy sets and systems based on AFS structure EI algebra and EII algebra. Fuzzy Sets Syst 95:179–188

    Article  MATH  Google Scholar 

  36. Liu XD, Pedrycz W (2007) The development of fuzzy decision trees in the framework of Axiomatic Fuzzy Set logic. Appl Soft Comput 7(1):325–342

    Article  Google Scholar 

  37. Liu XD, Liu WQ (2005) Credit rating analysis with AFS fuzzy logic. Lect Notes Comput Sci 3612:1198–1204

    Article  Google Scholar 

  38. Ding R, Liu XD, Chen Y (2006) The fuzzy clustering algorithm based on AFS topology. Lect Notes Artif Intell 4223:89–98

    Google Scholar 

  39. Li Y, Liu XD, Chen Y (2011) Selection of logistics center location using axiomatic fuzzy set and topsis methodology in logistics management. Expert Syst Appl 38:7901–7908

    Article  Google Scholar 

  40. Tao LL, Chen Y, Liu XD (2012) An integrated multiple criteria decision making model applying Axiomatic Fuzzy Set theory. Appl Math Model 36:5046–5058

    Article  MATH  Google Scholar 

  41. Angelo DME, Liu XD (2013) The use of axiomatic fuzzy set theory in AHP and TOPSIS methodology to determine strategies priorities by SWOT analysis. Qual Quant 47:2671–2685

    Article  Google Scholar 

  42. Liu XD, Pedrycz W (2009) Axiomatic fuzzy set theroy and its applications. Springer, Heidelberg

    Book  Google Scholar 

  43. Liu XD, Pedrycz W, Chai TY, Song ML (2009) The development of fuzzy rough sets with the use of structures and algebras of Axiomatic Fuzzy Sets. IEEE Trans Knowl Data Eng 21(3):443–462

    Article  Google Scholar 

  44. Wang YM, Luo Y (2010) Integration of correlations with standard deviations for determining attribute weights in multiple attribute decision making. Math Comput Model 51:1–12

    Article  MATH  MathSciNet  Google Scholar 

  45. Liu XD, Feng XH, Pedrycz W (2012) Extraction of fuzzy rules from fuzzy decision trees: an axiomatic fuzzy sets (AFS) approach. Data Knowl Eng 84:1–25

    Article  Google Scholar 

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Acknowledgments

Supported by the Natural Science Foundation of China (No. 61203283), the Open Project Program of Artificial Intelligence Key Laboratory of Sichuan Province (No. 2012RYJ02), Liaoning Provincial Natural Science Foundation of China (No. 2014025004) and the Fundamental Research Funds for the Central Universities (No. 3132014324). The authors would also like to acknowledge the financial support from China Scholarship Council.

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Authors and Affiliations

  1. Department of Mathematics, Dalian Maritime University, Dalian, 116026, China

    Xiaojuan Tian, Xiaodong Liu & Lidong Wang

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  1. Xiaojuan Tian
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  2. Xiaodong Liu
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  3. Lidong Wang
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Correspondence to Xiaojuan Tian.

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Tian, X., Liu, X. & Wang, L. An improved PROMETHEE II method based on Axiomatic Fuzzy Sets. Neural Comput & Applic 25, 1675–1683 (2014). https://doi.org/10.1007/s00521-014-1651-8

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  • DOI: https://doi.org/10.1007/s00521-014-1651-8

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