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A novel approach for fuzzy multi-criteria decision making / Hamed Mahmoud Elsayed Mahmoud ; Supervised Hesham Ahmed Hefny , Hisham Fouad Aly

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Hamed Mahmoud Elsayed Mahmoud , 2014Description: 135 Leaves ; 30cmOther title:
  • أسلوب مبتكر {uئإئ٩}تخاذ القرار الفازى متعدد المعايير [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Science Summary: This thesis proposes an improved fuzzy multi criteria decision making (FMCDM) model called: Gaussian fuzzy ANP (GFANP). The proposed GFANP overcomes the ranking problem of the classical FANP by introducing novel scenario for switching between TFNs and their approximated gaussian fuzzy numbers (GFNs) in the ranking stage, while returning back to TFNs when performing arithmetic operations during the preparation of evaluation matrices. Accordingly, the proposed GFANP model does not allow the appearance of zero values in the ranking vector of the considered alternatives. The proposed GFANP is evaluated by field experts in the domain of electric power generation, where we use our proposed model to select the best scenario for generating electric power in Egypt for the next decade based on both risk and cost
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Ha.N (Browse shelf(Opens below)) Not for loan 01010110064568000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.02.Ph.D.2014.Ha.N (Browse shelf(Opens below)) 64568.CD Not for loan 01020110064568000

Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Computer and Information Science

This thesis proposes an improved fuzzy multi criteria decision making (FMCDM) model called: Gaussian fuzzy ANP (GFANP). The proposed GFANP overcomes the ranking problem of the classical FANP by introducing novel scenario for switching between TFNs and their approximated gaussian fuzzy numbers (GFNs) in the ranking stage, while returning back to TFNs when performing arithmetic operations during the preparation of evaluation matrices. Accordingly, the proposed GFANP model does not allow the appearance of zero values in the ranking vector of the considered alternatives. The proposed GFANP is evaluated by field experts in the domain of electric power generation, where we use our proposed model to select the best scenario for generating electric power in Egypt for the next decade based on both risk and cost

Issued also as CD

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