scholarly journals A mathematical programming approach for equitable COVID-19 vaccine distribution in developing countries

Author(s):  
Madjid Tavana ◽  
Kannan Govindan ◽  
Arash Khalili Nasr ◽  
Mohammad Saeed Heidary ◽  
Hassan Mina
2008 ◽  
Vol 75 (1) ◽  
pp. 69-89 ◽  
Author(s):  
Hiroto Saigo ◽  
Sebastian Nowozin ◽  
Tadashi Kadowaki ◽  
Taku Kudo ◽  
Koji Tsuda

2021 ◽  
Author(s):  
Sheng-Hsing Nien ◽  
Liang-Hsuan Chen

Abstract This study develops a mathematical programming approach to establish intuitionistic fuzzy regression models (IFRMs) by considering the randomness and fuzziness of intuitionistic fuzzy observations. In contrast to existing approaches, the IFRMs are established in terms of five ordinary regression models representing the components of the estimated triangular intuitionistic fuzzy response variable. The optimal parameters of the five ordinary regression models are determined by solving the proposed mathematical programming problem, which is linearized to make the resolution process efficient. Based on the concepts of randomness and fuzziness in the formulation processes, the proposed approach can improve on existing approaches’ weaknesses with establishing IFRMs, such as the limitation of symmetrical triangular membership (or non-membership) functions, the determination of parameter signs in the model, and the wide spread of the estimated responses. In addition, some numerical explanatory variables included in the intuitionistic fuzzy observations are also allowed in the proposed approach, even though it was developed for intuitionistic fuzzy observations. In contrast to existing approaches, the proposed approach is general and flexible in applications. Comparisons show that the proposed approach outperforms existing approaches in terms of similarity and distance measures.


2014 ◽  
Vol 63 ◽  
pp. 674-680 ◽  
Author(s):  
S.D.O. Turner ◽  
D.A. Romero ◽  
P.Y. Zhang ◽  
C.H. Amon ◽  
T.C.Y. Chan

Sign in / Sign up

Export Citation Format

Share Document