Optimality conditions for fuzzy optimization problems under granular convexity concept

Author(s):  
Jianke Zhang ◽  
Xiaoyi Chen ◽  
Lifeng Li ◽  
Xiaojue Ma
2015 ◽  
Vol 15 (1) ◽  
pp. 57-73 ◽  
Author(s):  
Y. Chalco-Cano ◽  
W. A. Lodwick ◽  
R. Osuna-Gómez ◽  
A. Rufián-Lizana

Complexity ◽  
2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Nanxiang Yu ◽  
Dong Qiu

We propose the solution concepts for the fuzzy optimization problems in the quotient space of fuzzy numbers. The Karush-Kuhn-Tucker (KKT) optimality conditions are elicited naturally by introducing the Lagrange function multipliers. The effectiveness is illustrated by examples.


2021 ◽  
Vol 78 (1) ◽  
pp. 139-156
Author(s):  
Antonio Boccuto

Abstract We give some versions of Hahn-Banach, sandwich, duality, Moreau--Rockafellar-type theorems, optimality conditions and a formula for the subdifferential of composite functions for order continuous vector lattice-valued operators, invariant or equivariant with respect to a fixed group G of homomorphisms. As applications to optimization problems with both convex and linear constraints, we present some Farkas and Kuhn-Tucker-type results.


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