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An Efficient Neurodynamic Approach to Fuzzy Chance-constrained Programming.
- Source :
- International Journal on Artificial Intelligence Tools; Feb2021, Vol. 30 Issue 1, pN.PAG-N.PAG, 20p
- Publication Year :
- 2021
-
Abstract
- In both practical applications and theoretical analysis, there are many fuzzy chance-constrained optimization problems. Currently, there is short of real-time algorithms for solving such problems. Therefore, in this paper, a continuous-time neurodynamic approach is proposed for solving a class of fuzzy chance-constrained optimization problems. Firstly, an equivalent deterministic problem with inequality constraint is discussed, and then a continuous-time neurodynamic approach is proposed. Secondly, a sufficient and necessary optimality condition of the considered optimization problem is obtained. Thirdly, the boundedness, global existence and Lyapunov stability of the state solution to the proposed approach are proved. Moreover, the convergence to the optimal solution of considered problem is studied. Finally, several experiments are provided to show the performance of proposed approach. [ABSTRACT FROM AUTHOR]
- Subjects :
- LYAPUNOV stability
GOAL programming
CONVEX programming
PROBLEM solving
ALGORITHMS
Subjects
Details
- Language :
- English
- ISSN :
- 02182130
- Volume :
- 30
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- International Journal on Artificial Intelligence Tools
- Publication Type :
- Academic Journal
- Accession number :
- 148353762
- Full Text :
- https://doi.org/10.1142/S0218213021400017