International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 10  (October 2017), Pages:  26-32

Original Research Paper

Title: A Group decision making problem using hierarchical based fuzzy soft matrix approach

Author(s): Samsiah Abdul Razak 1, *, Daud Mohamad 2, Ini Imaina Abdullah 1

Affiliation(s):

1Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Perak Branch, Tapah Campus, 35400 Tapah Road, Perak, Malaysia
2Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, Shah Alam, 40450 Shah Alam, Selangor, Malaysia

https://doi.org/10.21833/ijaas.2017.010.005

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Abstract:

Fuzzy soft sets theory is a general mathematical tools to dealing with uncertainty problem. The matrix form has been introduced in fuzzy soft set and some of its properties have been discussed. However the theory of fuzzy soft set has been extensively used in many application, the importance weight of criteria has not been emphasized and thus is not incorporated in the calculation. The aim of this paper is to propose a selection procedure by group decision making in a hierarchical structure with fuzzy soft matrix. The lambda-max method is utilized in determining the criteria weight for the main and sub - criteria, while alternative decision will be solved by using fuzzy soft max-min decision making method. The hierarchical structure in Fuzzy AHP concept is applied to determine the overall priority vector, where the highest score is the desired alternative. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Fuzzy soft sets, Fuzzy soft matrix, Fuzzy soft hierarchical, Lambda-max method

Article History: Received 8 June 2017, Received in revised form 3 August 2017, Accepted 8 August 2017

Digital Object Identifier: 

https://doi.org/10.21833/ijaas.2017.010.005

Citation:

Razak SA, Mohamad D, and Abdullah II (2017). A Group decision making problem using hierarchical based fuzzy soft matrix approach. International Journal of Advanced and Applied Sciences, 4(10): 26-32

Permanent Link:

http://www.science-gate.com/IJAAS/V4I10/Razak.html

References (16)

  1. Çağman N and Enginoğlu S (2010a). Soft set theory and uni–int decision making. European Journal of Operational Research, 207(2): 848-855. https://doi.org/10.1016/j.ejor.2010.05.004 
  2. Çağman N and Enginoğlu S (2010b). Soft matrix theory and its decision making. Computers and Mathematics with Applications, 59(10): 3308-3314. https://doi.org/10.1016/j.camwa.2010.03.015 
  3. Çağman N and Enginoğlu S (2012). Fuzzy soft matrix theory and its application in decision making. Iranian Journal of Fuzzy Systems, 9(1): 109-119. 
  4. Carlsson C and Fullér R (1996). Fuzzy multiple criteria decision making: Recent developments. Fuzzy Sets and Systems, 78(2): 139-153. https://doi.org/10.1016/0165-0114(95)00165-4 
  5. Celik Y and Celik IA (2016). Framework for medical diagnosis via fuzzy soft matrices. New Trend in Mathematical Sciences, 4(2): 248-256. https://doi.org/10.20852/ntmsci.2016218261 
  6. Chetia B and Das PK (2010). An application of interval-valued fuzzy soft. International Journal of Contemporary Mathematical Sciences, 5(38): 1887-1894.     
  7. Csutora R and Buckley JJ (2001). Fuzzy hierarchical analysis: the Lambda-Max method. Fuzzy Sets and Systems, 120(2): 181-195. https://doi.org/10.1016/S0165-0114(99)00155-4 
  8. Hambali A, Sapuan SM, Ismail N, and Nukman Y (2009). Application of analytical hierarchy process in the design concept selection of automotive composite bumper beam during the conceptual design stage. Scientific Research and Essays, 4(4): 198-211.     
  9. Herawan T and Deris MM (2010). Soft decision making for patients suspected influenza. In the International Conference on Computational Science and Its Applications, Springer, Berlin, Heidelberg: 405-418. https://doi.org/10.1007/978-3-642-12179-1_34 
  10. Maji PK, Biswas R, and Roy AR (2001). Intuitionistic fuzzy soft sets. Journal of Fuzzy Mathematics, 9(3), 589-602.     
  11. Maji PK, Roy AR, and Biswas R (2002). An application of soft sets in a decision making problem. Computers and Mathematics with Applications, 44(8-9): 1077-1083. https://doi.org/10.1016/S0898-1221(02)00216-X 
  12. Molodtsov D (1999). Soft set theory—first results. Computers and Mathematics with Applications, 37(4-5): 19-31. https://doi.org/10.1016/S0898-1221(99)00056-5 
  13. Razak S and Mohamad D (2012). Aplikasi Matrik Lembut dalam Masalah Pembuatan Keputusan Secara Berkumpulan [An Application of Soft Matrices in Group Decision Making Problems]. Menemui Matematik [Discovering Mathematics], 34(1): 33–39.     
  14. Roy AR and Maji PK (2007). A fuzzy soft set theoretic approach to decision making problems. Journal of Computational and Applied Mathematics, 203(2): 412-418. https://doi.org/10.1016/j.cam.2006.04.008 
  15. Wei YANG (2010). Fuzzy soft matrix and its lattice structure [J]. Journal of Liaoning Technical University (Natural Science), Jiangxi University of Technology, Nanchang, China. Available online at: http://en.cnki.com.cn/Article_en/CJFDTOTAL-FXKY201005006.htm 
  16. Yang Y and Ji C (2011). Fuzzy soft matrices and their applications. In the International Conference on Artificial Intelligence and Computational Intelligence, Springer, Berlin, Heidelberg: 618-627.  https://doi.org/10.1007/978-3-642-23881-9_79