Fuzzy random chance-constrained programming

Author

Liu, Baoding

Author_Institution

Dept. of Math. Sci., Tsinghua Univ., Beijing, China

Volume

9

Issue

5

fYear

2001

fDate

10/1/2001 12:00:00 AM

Firstpage

713

Lastpage

720

Abstract

By fuzzy random programming, we mean the optimization theory dealing with fuzzy random decision problems. This paper presents a new concept of chance of fuzzy random events, and constructs a general framework of fuzzy random chance-constrained programming. We also design a spectrum of fuzzy random simulations for computing uncertain functions arising in the area of fuzzy random programming. To speed up the process of handling uncertain functions, we train a neural network to approximate uncertain functions based on the training data generated by fuzzy random simulation. Finally, we integrate the fuzzy random simulation, neural network, and genetic algorithm to produce a more powerful and effective hybrid intelligent algorithm for solving fuzzy random programming models and illustrate its effectiveness by some numerical examples

Keywords

function approximation; fuzzy set theory; genetic algorithms; minimax techniques; neural nets; random processes; stochastic programming; chance constrained programming; function approximation; genetic algorithm; hybrid intelligent algorithm; minimax model; neural network; simulation; stochastic programming; terms fuzzy programming; Computational modeling; Functional programming; Fuzzy neural networks; Fuzzy sets; Fuzzy systems; Genetic algorithms; Intelligent networks; Linear programming; Neural networks; Stochastic processes;

fLanguage

English

Journal_Title

Fuzzy Systems, IEEE Transactions on

Publisher

ieee

ISSN

1063-6706

Type

jour

DOI

10.1109/91.963757

Filename

963757