کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4942919 1437615 2018 18 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Modification of the Best-Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers
ترجمه فارسی عنوان
اصلاح بهترین و بدترین روش های MABAC: رویکرد جدید مبتنی بر اعداد فازی سخت با ضریب فزاینده
کلمات کلیدی
تجزیه و تحلیل چند معیاره؛ مجموعه های فازی؛ اعداد سخت ؛ بهترین و بدترین روش؛ MABAC
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


- Interval rough number is introduced to deal with the vagueness in decision-making.
- A novel multi-criteria model based on interval rough numbers is proposed.
- Multi-criteria techniques were compared based on interval rough and fuzzy approaches.

This paper presents a new approach for the treatment of uncertainty which is based on interval-valued fuzzy-rough numbers (IVFRN). It is shown that by integrating the rough approach with the traditional fuzzy approach, the subjectivity that exists when defining the borders of fuzzy sets is eliminated. IVFRN make decision making possible using only the internal knowledge in the operative data available to the decision makers. In this way objective uncertainties are used and there is no need to rely on models of assumptions. Instead of different external parameters in the application of IVFRN, the structure of the given data is used. On this basis an original multi-criteria model was developed based on an IVFRN approach. In this multi-criteria model the traditional steps of the BWM (Best-Worst method) and MABAC (Multi-Attributive Border Approximation area Comparison) methods are modified. The model was tested and validated on a study of the optimal selection of fire fighting helicopters. Testing demonstrated that the model based on IVFRN enabled more objective expert evaluation of the criteria in comparison with traditional fuzzy and rough approaches. A sensitivity analysis of the IVFRN BWM-MABAC model was carried out by means of 57 scenarios, the results of which showed a high degree of stability. The results of the IVFRN model were validated by comparing them with the results of the fuzzy and rough extension of the MABAC, COPRAS and VIKOR models.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 91, January 2018, Pages 89-106
نویسندگان
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