sensitivity and stability analysis
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Author(s):  
Deepak Mahla ◽  
Shivi Agarwal ◽  
Trilok Mathur

The slack-based measure (SBM) DEA model is a non-radial model used to calculate the relative efficiency, input, and output targets of the different decision-making units (DMUs) based on their best peers or efficient frontier. The conventional SBM DEA model used crisp inputs and outputs. But, it can be observed in real-life problems that sometimes the available data is in linguistic forms such as ‘few,’ ‘many,’ ‘small,’ or missing data. The DEA technique is frontier based, and therefore, imprecise data may lead to untenable results. Fuzzy theory, which is already established to handle uncertain data, can overcome this problem. Furthermore, the sensitivity and stability analysis have been checked the robustness of fuzzy DEA models. In this study, sensitivity and stability analysis of the fuzzy SBM DEA has been performed. The lower and upper sensitive bounds for inputs and outputs variables have been obtained for both the inefficient and efficient DMUs to calculate the input and output targets. Finally, a real-life transportation problem for the validity of the study is presented for its depiction.


2020 ◽  
Vol 14 (6) ◽  
pp. 986-996 ◽  
Author(s):  
Muhammad Saeed Uz Zaman ◽  
Syed Basit Ali Bukhari ◽  
Raza Haider ◽  
Muhammad Omer Khan ◽  
Shazia Baloch ◽  
...  

2019 ◽  
Vol 37 (4) ◽  
pp. 5777-5796 ◽  
Author(s):  
Azizollah Nosrat ◽  
Masoud Sanei ◽  
Ali Payan ◽  
Farhad Hosseinzadeh Lotfi ◽  
Shabnam Razavyan

2019 ◽  
Vol 109 (3) ◽  
pp. 959-975 ◽  
Author(s):  
Aglaja Blanke ◽  
Grzegorz Kwiatek ◽  
Patricia Martínez‐Garzón ◽  
Marco Bohnhoff

2019 ◽  
Vol 9 (1) ◽  
pp. 47-53
Author(s):  
Robiatul Witari Wilda ◽  
◽  
Trisilowati Trisilowati ◽  
Moch. Aruman Imron

2015 ◽  
Vol 10 (4) ◽  
pp. 737-752 ◽  
Author(s):  
Feng He ◽  
Xiaoning Xu ◽  
Rong Chen ◽  
Na Zhang

2015 ◽  
Vol 2015 ◽  
pp. 1-31 ◽  
Author(s):  
Zhenzhen Shi ◽  
Chih-Hang J. Wu ◽  
David Ben-Arieh ◽  
Steven Q. Simpson

Sepsis is a systemic inflammatory response (SIR) to infection. In this work, a system dynamics mathematical model (SDMM) is examined to describe the basic components of SIR and sepsis progression. Both innate and adaptive immunities are included, and simulated resultsin silicohave shown that adaptive immunity has significant impacts on the outcomes of sepsis progression. Further investigation has found that the intervention timing, intensity of anti-inflammatory cytokines, and initial pathogen load are highly predictive of outcomes of a sepsis episode. Sensitivity and stability analysis were carried out using bifurcation analysis to explore system stability with various initial and boundary conditions. The stability analysis suggested that the system could diverge at an unstable equilibrium after perturbations ifrt2max(maximum release rate of Tumor Necrosis Factor- (TNF-)αby neutrophil) falls below a certain level. This finding conforms to clinical findings and existing literature regarding the lack of efficacy of anti-TNF antibody therapy.


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