Genetic-based fuzzy adaptation

Author

Dadone, Paolo ; VanLandingham, Hugh F.

Author_Institution

Bradley Dept. of Electr. Eng., Virginia Polytech. Inst. & State Univ., Blacksburg, VA, USA

Volume

2

fYear

1998

fDate

4-9 May 1998

Firstpage

1094

Abstract

A novel paradigm for adaptation in discrete event dynamic systems control is presented. In this approach a few optimal control policies are used to train an adaptation module capable of generalizing over several operating conditions. The general idea is then applied, through simulations, to an inventory system. A fuzzy adaptation module is built from a few optimal examples generated using a genetic algorithm. The fuzzy module is then capable of adapting the inventory policy achieving much better results than a static policy

Keywords

adaptive control; discrete event systems; fuzzy control; genetic algorithms; optimal control; stock control; adaptation module; discrete event dynamic systems; genetic algorithm; genetic-based fuzzy adaptation; inventory system; optimal control policies; Artificial neural networks; Control systems; Fuzzy systems; Genetic algorithms; Learning; Manufacturing systems; Optimal control; Power system modeling; Telecommunication traffic; Traffic control;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on

Conference_Location

Anchorage, AK

ISSN

1098-7584

Print_ISBN

0-7803-4863-X

Type

conf

DOI

10.1109/FUZZY.1998.686271

Filename

686271