A Computational Model for Multi-level Quadratically Constrained Quadratic Optimization under Fully Fuzzy Environment

2018 ◽  
Vol 27 (5) ◽  
pp. 1-21 ◽  
Author(s):  
Hawaf AbdAlhakim ◽  
O Emam ◽  
A El-Mageed
2021 ◽  
pp. 1-23
Author(s):  
Moussa BARRO ◽  
Satafa SANOGO ◽  
Mohamed ZONGO ◽  
Sado TRAORÉ

Robust Optimization (RO) arises in two stages of optimization, first level for maximizing over the uncertain data and second level for minimizing over the feasible set. It is the most suitable mathematical optimization procedure to solve real-life problem models. In the present work, we characterize robust solutions for both homogeneous and non-homogeneous quadratically constrained quadratic optimization problem where constraint function and cost function are uncertain. Moreover, we discuss about optimistic dual and strong robust duality of the considered uncertain quadratic optimization problem. Finally, we complete this work with an example to illustrate our solution method. Mathematics Subject Classification: (2010) 90C20 - 90C26 - 90C46-90C47 Keywords: Robust Optimization, Data Uncertainty, Quadratic Optimization Strong Duality, Robust Solution, DPJ-Convex.


2020 ◽  
Vol 78 (3) ◽  
pp. 423-451
Author(s):  
Ramtin Madani ◽  
Mohsen Kheirandishfard ◽  
Javad Lavaei ◽  
Alper Atamtürk

2001 ◽  
Vol 61 (8) ◽  
pp. 1017-1040 ◽  
Author(s):  
Prasanna Raghavan ◽  
Suresh Moorthy ◽  
Somnath Ghosh ◽  
N.J. Pagano

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