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العنوان
Combining Multiple Criteria Decision-Making Methods And Single Valued Neutrosophic Sets For Solving Alternatives Ranking Problem \
المؤلف
El-Shabshery, Aliaa Abd El-Rahman Mahmoud.
هيئة الاعداد
باحث / علياء عبد الرحمن محمود الشبشيري
مشرف / محمد فتوح عبد الحميد داود
مناقش / أحمد محمد القصاص
مناقش / رزق مسعود رزق الله
الموضوع
Multiple Criteria Decision Making. Decision Support Systems. Decision Making - Data Processing. Decision Making - Mathematical Models. Neutrosophic Logic.
تاريخ النشر
2021.
عدد الصفحات
102 p. :
اللغة
الإنجليزية
الدرجة
ماجستير
التخصص
الهندسة الميكانيكية
تاريخ الإجازة
29/11/2021
مكان الإجازة
جامعة المنوفية - كلية الهندسة - هندسة الانتاج والتصميم الميكانيكي
الفهرس
Only 14 pages are availabe for public view

from 102

from 102

Abstract

Information measures have received more care in the latest years. In this
work, the multi-criteria decision-making (MCDM) problem based on single-valued neutrosophic set (SVNS) information measures is presented. Some definitions of information measures are first introduced. These include cross-entropy, aggregation operators, cosine similarity measure,
subtraction operational averaging operator, and correlation coefficient. A
numerical case study (metal stamping layout selection problem) is provided
in which the criteria values are described in exact (crisp) values form. Firstly, the decision matrix is fuzzified and then transformed into an SVNS set (Neutrosophication). The entropy method is considered to define the criterion weights. The result of the existing SVNS information measures used in this work is compared with the published results to validate the accuracy grounded on the same illustrative example presented in this work and then highpoints the benefits of various methods over alternative methods. Spearman’s rank correlation coefficient among the compared results is applied to determine how strong the relationship between them is. The comparative analysis defines the applicability and usefulness of the used SVNS information measures. An extended technique for the VIKOR method with SVNS is also proposed to solve the same case study. Different weight methods for calculating the criteria weights in the case of being completely unknown in
the VIKOR method under the SVNS environment are applied. A nonlinear optimization model grounded on the maximizing deviation method is constructed, and a nonlinear optimization model grounded on the VIKOR method is also constructed, to objectively decide the best criterion weights. Sensitivity analysis plots are considered for the results of the same case study to show how many input parameters can be changed to monitor the overall effects on the final ranking of alternatives and also to test the reliability of decisions.