Fuzzy Multi-Feature Decision Making and Its Applications

Document Type : Original Article

Authors

20.1001.1.27174409.1399.3.1.10.5/DOR

Abstract

One of the most important parts of expert systems and operations research is multi-criteria fuzzy decision making in which the decision-making process is based on several different criteria and most of these criteria are in conflict with each other. Fuzzy decision making is commonly used in situations where vague and incomplete information on problem solutions is available. In this paper, we will examine fuzzy multiphase decision making and its various algorithms with a focus on fuzzy TOPSIS algorithm and then examine the various applications of fuzzy multiphase decision algorithms.

Keywords

References

[1] R. Ali, M. Nikolic, and A. Zahra. (2017) Personnel selection using group fuzzy AHP and SAW methods, J. Eng. Manag. Compet., vol. 7, no. 1, pp. 3-10.
 
[2] Z. Allah Bukhsh, I. Stipanovic, G. Klanker, A. O' Connor, and A. G. Doree. (2019) Network level bridges maintenance planning using Multi-Attribute Utility Theory. Struct. Infrastruct. Eng., vol. 15, no. 7, pp. 872-885.
 
[3] G. Arslan and Ö. AydIn, “On a software for fuzzy MCDM. (2008) On a software for fuzzy MCDM.in 20th International Conference EURO Mini Conference "Continuous Optimization and Knowledge-Based Technologies", EurOPT, pp. 211-216.
 
[4] H. Bayati, MB. Dowlatshahi and M. Paniri. (2020) MLCR: MLPSO: A Filter Multi-label Feature Selection Based on Particle Swarm Optimization. In: 2020 25th International Computer Conference, Computer Society of Iran (CSICC). IEEE, pp 1–6.
 
[5] M. Behzadian, S. Khanmohammadi Otaghsara, M. Yazdani, and J. Ignatius. (2012) A state-of the-art survey of TOPSIS applications. Expert Systems with Applications, vol. 39, no. 17. pp. 13051–13069.
 
[6] R. E. Bellman and L. A. Zadeh. (1970) on-Making in a Fuzzy Environment. Manage. Sci., vol. 17, no. 4, p. B-141-B-164.
 
[7] S. Bigaret, R. E. Hodgett, P. Meyer, T. Mironova, and A. L. Olteanu. (2017) Supporting the multi-criteria decision aiding process: R and the MCDA package.EURO J. Decis. Process., vol. 5, no. 1–4, pp. 169–194.
 
[8] S. Çalı and Ş. Y. Balaman. (2019)A novel outranking based multi criteria group decision making methodology integrating ELECTRE and VIKOR under intuitionistic fuzzy environment. Expert Syst. Appl., vol. 119, pp. 36–50.
 
[9] T. H. Chang. (2014) Fuzzy VIKOR method: A case study of the hospital service evaluation in Taiwan. Inf. Sci. (Ny)., vol. 271, pp. 196-212.
 
[10] P. Chen. (2019) Effects of normalization on the entropy-based TOPSIS method. Expert Syst. Appl., vol. 136, pp. 33-41.
 
[11] S.-J. Chen and C.-L. Hwang. (1992) Fuzzy Multiple Attribute Decision Making Methods. 1992, pp. 289–486.
 
[12] T. C. Chu. (2012) Selecting plant location via a fuzzy TOPSIS approach. Int. J. Adv. Manuf. Technol., vol. 20, no. 11, pp. 859-864.
 
[13] T. C. Chu and H. T. Le. (2019) An extension to fuzzy ELECTRE," Soft Comput.
 
[14] A. Debnath, M. Majumder, and M. Pal. (2016) Potential of Fuzzy-ELECTRE MCDM in Evaluation of Cyanobacterial Toxins Removal Methods. rab. J. Sci. Eng., vol. 41, no. 10, pp. 3931–3944.
 
[15] MB. Dowlatshahi, V. Derhami, and H. Nezamabadi-pour. (2020) Fuzzy particle swarm optimization with nearest-better neighborhood for multimodal optimization. Iran J Fuzzy Syst, vol. 17, pp. 7-24.
 
[16] R. Faia, T. Pinto, O. Abrishambaf, F. Fernandes, Z. Vale, and J. M. Corchado. (2017) Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy management. Energy Build., vol. 155, pp. 269–281.
 
[17] M. R. Feylizadeh and M. Bagherpourl. (2018) Manufacturing performance measurement using fuzzy multi-attribute utility theory and Z-number. Trans. Famena, vol. 42, no. 1, pp. 37–49.
 
[18] R. Garg and D. Jainl. (2016) Fuzzy multi-attribute decision making evaluation of e-learning websites using FAHP, COPRAS, VIKOR, WDBA. Decis. Sci. Lett., vol. 6, no. 4, pp. 351–364.
 
[19] M. Gul, M. F. Ak, and A. F. Guneril. (2019) Pythagorean fuzzy VIKOR-based approach for safety risk assessment in mine industry. J. Safety Res., vol. 69, pp. 135-153.
 
[20] M. Gul, E. Celik, N. Aydin, A. Taskin Gumus, and A. F. Guneri. (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Applied Soft Computing Journal, vol. 46. pp. 60–89.
 
[21] A. Hatami-Marbini and F. Kangi. (2017) An extension of fuzzy TOPSIS for a group decision making with an application to tehran stock exchange. Appl. Soft Comput. J., vol. 52, pp. 1084–1097.
 
[22] A. Hashmi and MB. Dowlatshahi. (2020) MLCR: A Fast Multi-label Feature Selection Method Based on K-means and L2-norm. In: 2020 25th International Computer Conference, Computer Society of Iran (CSICC). IEEE, pp 1-7.
 
[23] A. Hashmi, MB. Dowlatshahi and H. Nezamabadi-pour. (2020) MGFS: A multi-label graph-based feature selection algorithm via PageRank centrality. Expert Syst Appl, vol. 142, pp.113024.
 
[24] J.-J. Huang. (2011) Simple Additive Weighting Method," in Multiple Attribute Decision Making. pp. 55–67.
 
[25] C.-L. Hwang and K. Yoon. (1981) Methods for Multiple Attribute Decision Making. pp. 58-191.
 
[26] N. M. Ishak, M. R. Mansor, and S. D. Malingam. (2016) Selection of natural fibre reinforced composites using fuzzy VIKOR for car front hood. Int. J. Mater. Prod. Technol., vol. 53, no. 3/4, p. 267.
 
[27] A. Jiménez, A. Mateos, and P. Sabio. (2013) Dominance intensity measure within fuzzy weight oriented MAUT: An application. Omega, vol. 41, no. 2, pp. 397–405.
 
[28] C. Kahraman, S. C. Onar, and B. Oztaysi. (2015) Fuzzy Multicriteria Decision-Making: A Literature Review. nternational Journal of Computational Intelligence Systems, vol. 8, no. 4. pp. 637–666.
 
[29] M. N. B. Kore, K. Ravi, and S. B. Patil. (2017) A Simplified Description of FUZZY TOPSIS Method for Multi Criteria Decision Making. Int. Res. J. Eng. Technol., vol. 4, no. 5, pp. 2395–56.
 
[30] Y. Melia. (2016) Multi Attribute Decision Making Using Simple Additive Weighting and Weighted Product in Investment Introduction. Int. Acad. J. Bus. Manag., vol. 3, no. 7, pp. 4-5.
 
[31] A. Memari, A. Dargi, M. R. Akbari Jokar, R. Ahmad, and A. R. Abdul Rahim. (2019) Sustainable supplier selection: A multi-criteria intuitionistic fuzzy TOPSIS method. J. Manuf. Syst., vol. 50, pp. 9–24.
 
[32] I. Mukhametzyanov. (2020) MCDM tools. (https://www.mathworks.com/matlabcentral/fileexchange/65742-mcdm-tools), MATLAB Central File Exchange.
 
[33] S. NĂDĂban, S. Dzitac, and I. Dzitac. (2016) Fuzzy TOPSIS: A General View,” in Procedia Computer Science. vol. 91, pp. 823–831.
 
[34] A. T. Nursal, M. F. Omar, and M. N. M. Nawi. (2016) The application of fuzzy topsis to the selection of building information modeling software. J. Telecommun. Electron. Comput. Eng., vol. 10, no. 1-10, pp. 1-10.
 
[35] M. Paniri, MB. Dowlatshahi and H. Nezamabadi-pour. (2020) MLACO: A multi-label feature selection algorithm based on ant colony optimization. Knowledge-Based Syst, vol. 192, pp. 105285.
 
[36] G.-K. Park and J. L. R. Benedictos. (2006) Ship's Collision Avoidance Support System Using Fuzzy-CBR. J. Korean Inst. Intell. Syst., vol. 16, no. 5, pp. 635–641.
 
[37] J. Rezaei. (2015) Best-worst multi-criteria decision-making method. Omega (United Kingdom), vol. 53, pp. 49–57.
 
[38] J. Rezaei, P. B. M. Fahim, and L. Tavasszy. (2014) Supplier selection in the airline retail industry using a funnel methodology: Conjunctive screening method and fuzzy AHP. Expert Syst. Appl., vol. 41, no. 18, pp. 8165–8179.
 
[39] E. Roszkowska and D. Kacprzak. (2016) The fuzzy saw and fuzzy TOPSIS procedures based on ordered fuzzy numbers. Inf. Sci. (Ny)., vol. 369, pp. 564-584.
 
[40] T. L. Saaty. (1980) The analytic hierarchy process: planning. Prior. Setting. Resour. Alloc. MacGraw-Hill, New York Int. B. Co., p. 287.
 
[41] P. H. Dos Santos, S. M. Neves, D. O. Sant'Anna, C. H. de Oliveira, and H. D. Carvalho. (2019) The analytic hierarchy process supporting decision making for sustainable development: An overview of applications. Journal of Cleaner Production, vol. 212. pp. 119–138.
 
[42] Ü. Şengül, M. Eren, S. Eslamian Shiraz, V. Gezder, and A. B. Sengül. (2015) Fuzzy TOPSIS method for ranking renewable energy supply systems in Turkey. Renew. Energy, vol. 75, pp. 617-625.
 
[43] B. Vahdani and H. Hadipour. (2011) Extension of the ELECTRE method based on interval-valued fuzzy sets. Soft Comput., vol. 15, no. 3, pp. 569–579.
 
[44] M. Velasquez and P. Hester. (2013) An analysis of multi-criteria decision making methods. Int. J. Oper. Res., vol. 10, no. 2, pp. 56–66.
 
[45] W. Waziana, R. Irviani, I. Oktaviani, F. Satria, D. Kurniawan, and A. Maseleno. (2018) Fuzzy Simple Additive Weighting for Determination of Recipients Breeding Farm Program. Int. J. Pure Appl. Math., vol. 118, no. 7 Special Issue.
 
[46] M. C. Wu, Y. F. Lo, and S. H. Hsu. (2008) A fuzzy CBR technique for generating product ideas. Expert Syst. Appl., vol. 34, no. 1, pp. 530–540.
 
[47] X. Yu, S. Zhang, X. Liao, and X. Qi. (2018) ELECTRE methods in prioritized MCDM environment. Inf. Sci. (Ny)., vol. 424, pp. 301-316.
 
[48] . H. Zyoud, L. G. Kaufmann, H. Shaheen, S. Samhan, and D. Fuchs-Hanusch (2016) A framework for water loss management in developing countries under fuzzy environment: Integration of Fuzzy AHP with Fuzzy TOPSIS. Expert Syst. Appl., vol.61, pp. 86–105.
 
[49] B. O'Neill, Semi-Riemannian geometry, Academic Press, 1986.
 
[50] J. Oprea, Differential geometry and its applications, Prentice Hall, second ed., 2004.

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History

  • Receive Date: 09 April 2020
  • Revise Date: 24 July 2020
  • Accept Date: 01 February 2021

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