Modelling and optimization for a type of fuzzy nonlinear programming problems in manufacturing systems

Author

Jiafu Tang ; Dingwei Wang

Author_Institution

Dept. of Autom. Control, Northeastern Univ., Liaoning, China

Volume

4

fYear

1996

fDate

13-13 Dec. 1996

Firstpage

4401

Abstract

A model for a type of fuzzy nonlinear programming problems (FNP) is proposed. This paper develops an inexact approach to solve this type model of nonlinear programming problems. Instead of finding an exact optimal solution. This approach uses a genetic algorithm (GA) with mutation along the weighted gradient direction to find a family of solutions with acceptable membership degrees. Then by means of human-computer interaction, the solution preferred by the decision maker (DM) under different criteria can be achieved.

Keywords

decision theory; fuzzy set theory; genetic algorithms; manufacturing resources planning; nonlinear programming; production control; decision maker; fuzzy nonlinear programming problems; genetic algorithm; human-computer interaction; inexact approach; manufacturing systems; membership degrees; mutation; weighted gradient direction; Automatic programming; Delta modulation; Fuzzy control; Fuzzy systems; Genetic mutations; Job shop scheduling; Mathematical programming; Optimization methods; Production systems; Virtual manufacturing;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1996., Proceedings of the 35th IEEE Conference on

Conference_Location

Kobe, Japan

ISSN

0191-2216

Print_ISBN

0-7803-3590-2

Type

conf

DOI

10.1109/CDC.1996.577485

Filename

577485