Fuzzy entropy based MOORA model for selecting material for mushroom in viet nam

Fuzzy entropy based MOORA model for selecting material for mushroom in viet nam

Автор: Tran Trung Hieu, Nguyen Xuan Thao

Журнал: International Journal of Information Engineering and Electronic Business @ijieeb

Статья в выпуске: 5 vol.11, 2019 года.

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The role of materials in the proper design and operation of products has been acknowledged. An incorrectly selected material for a certain product may cause premature failure of the final product. The right choice of available materials is very important to the success and competitiveness of manufacturing organizations. In Vietnam, tropical monsoon climate conditions greatly affect mushroom cultivation. The raw materials, additives and the ratio between them will also affect the quality and yield of mushrooms. Therefore, selecting the options for growing mushrooms or choosing good materials to grow mushrooms effectively is also a matter of concern. This is a problem of many decision-making problems. In this paper we multi-objective optimization on the basis of ratio analysis (MOORA) method to evaluate mushroom cultivation options in Vietnam.

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MOORA method, Mushroom, FMCDM, entropy

Короткий адрес: https://sciup.org/15016185

IDR: 15016185   |   DOI: 10.5815/ijieeb.2019.05.01

Список литературы Fuzzy entropy based MOORA model for selecting material for mushroom in viet nam

  • TBT Nguyen, XN Ngo, TT Nguyen, DA Tran, XC Nguyen, VG Nguyen and TD Tran (2016) Evaluating the Growth and Yield of King Oyster Mushroom (Pleurotus eryngii (DC.:Fr.) Quél) on Different Substrates. Vietnam J.Agri.Sci. 2016, Vol. 14, No. 5: 816-823.
  • Brauers WKM (2004). Optimization methods for a stakeholder society. A revolution in economic thinking by multi-objective optimization. Boston: Kluwer Academic Publishers; 2004.
  • VT Le, TNM Nguyen and VD Mai (2015). Effects of some potential agro-based wastes in Mekong Delta on the growth of Pleurotus sajorcaju, Tạp chí khoa học Đại học Cần thơ, 39: 36-43.
  • Karande P and Chakraborty S (2012). Application of multi-objective optimization on the basis of ratio analysis (MOORA) method for materials selection. Materials & Design, 37, 317-324.
  • Sharma S., Yadav R.K.P. and C.P. Pokhrel (2013). Growth and yield of oyster mushroom (Pleurotus ostreatus) on different substrates. Journal on New Biological Reports 2(1): 03-08.
  • Kiong, S. C., Lee, L. Y., Chong, S. H., Azlan, M. A., Nor, M., & Hisyamudin, N. (2013). Decision making with the analytical hierarchy process (AHP) for material selection in screw manufacturing for minimizing environmental impacts. In Applied Mechanics and Materials 315: 57-62.
  • Mayyas, A., Omar, M. A., & Hayajneh, M. T. (2016). Eco-material selection using fuzzy TOPSIS method. International Journal of Sustainable Engineering, 9(5), 292-304.
  • Jayakrishna, K., & Vinodh, S. (2017). Application of grey relational analysis for material and end of life strategy selection with multiple criteria. International Journal of Materials Engineering Innovation, 8(3-4), 250-272.
  • Jahan, A., Mustapha, F., Ismail, M. Y., Sapuan, S. M., & Bahraminasab, M. (2011). A comprehensive VIKOR method for material selection. Materials & Design, 32(3), 1215-1221.
  • Gadakh, V. S., Shinde, V. B., Khemnar, N. S., & Kumar, A. (2016, December). Application of MOORA Method for Friction Stir Welding Tool Material Selection. In Techno-Societal 2016, International Conference on Advanced Technologies for Societal Applications (pp. 845-854). Springer, Cham.
  • Chakraborty, S., & Chatterjee, P. (2013). Selection of materials using multi-criteria decision-making methods with minimum data. Decision Science Letters, 2(3), 135-148.
  • Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
  • Petković, D., Madić, M., Radovanović, M., & Janković, P. (2015). Application of Recently Developed MCDM Methods for Materials Selection. In Applied Mechanics and Materials Vol. 809, pp. 1468-1473.
  • Bhowmik, C., Gangwar, S., Bhowmik, S., & Ray, A. (2018). Selection of Energy-Efficient Material: An Entropy–TOPSIS Approach. In Soft Computing: Theories and Applications (pp. 31-39). Springer, Singapore.
  • Al-Sharhan, S., Karray, F., Gueaieb, W., & Basir, O. (2001). Fuzzy entropy: a brief survey. In 10th IEEE International Conference on Fuzzy Systems.(Cat. No. 01CH37297) (Vol. 3, pp. 1135-1139). IEEE.
  • Nguyen, X. T., & Nguyen, D. D. (2014). Rough fuzzy relation on two universal sets. International Journal of Intelligent Systems and Applications, 6(4), 49-55.
  • Nguyen, X. T. (2015). Support-intuitionistic fuzzy set: a new concept for soft computing. International Journal of Intelligent Systems and Applications, 7(4), 11-16.
  • Thao, N. X., Smarandache, F., & Dinh, N. V. (2017). Support-Neutrosophic Set: A New Concept in Soft Computing. Neutrosophic Sets Syst, 16, 93-98.
  • Van Dinh, N., & Thao, N. X. (2018). Some measures of picture fuzzy sets and their application in multi-attribute decision making. Int. J. Math. Sci. Comput.(IJMSC), 4(3), 23-41.
  • Le, N. T., Van Nguyen, D., Ngoc, C. M., & Nguyen, T. X. (2018). NEW DISSIMILARITY MEASURES ON PICTURE FUZZY SETS AND APPLICATIONS. Journal of Computer Science and Cybernetics, 34(3), 219-231.
  • Nguyen, X. T. (2018). Evaluating Water Reuse Applications under Uncertainty: A Novel Picture Fuzzy Multi Criteria Decision Making Medthod. International Journal of Information Engineering and Electronic Business, 10(6), 32-39.
  • Nguyen, X. T., Nguyen, V. H., & Garg, H (2017) Exponential similarity measures for Pythagorean fuzzy sets and their applications to pattern recognition and decision-making process. Complex & Intelligent Systems, V5 (2),217-228.
  • Thao, N. X., & Smarandache, F. (2018). Divergence Measure of Neutrosophic Sets and Applications. Neutrosophic Sets and Systems, 142-152.
  • Nhung L.T. and Nguyen.X. T (2019) A Novel Multi-Criteria Decision Making Method for Evaluating Water Reuse Applications under Uncertaint. Vietnam Journal of Agricultural Sciences, V1(3), 230-239.
  • Thao, N. X., Ali, M., & Smarandache, F. (2019). An intuitionistic fuzzy clustering algorithm based on a new correlation coefficient with application in medical diagnosis. Journal of Intelligent & Fuzzy Systems, Vol36(1), 189-198.
  • Xuan Thao, N. (2018). A new correlation coefficient of the intuitionistic fuzzy sets and its application. Journal of Intelligent & Fuzzy Systems, V35(2), 1959-1968.
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