Study uncertain information job shop scheduling problem based on rough sets

Author

Yuan-Rong, He ; Lin, Lu

Author_Institution

Sch. of Info-Phys. & Geomatics Eng., Central South Univ., Changsha, China

Volume

4

fYear

2009

fDate

8-9 Aug. 2009

Firstpage

79

Lastpage

82

Abstract

Uncertain information job shop scheduling problem is very common in flexible manufacturing in modern manufacturing industry. The paper uses rough sets theory to establish rough programming scheduling model of such problem, which reflects the uncertain situation in workshop more truly than other scheduling models, and proposes a new rough neural network to solve these complex problems. The simulation tests prove the effectiveness of the models.

Keywords

flexible manufacturing systems; job shop scheduling; neural nets; rough set theory; uncertain systems; flexible manufacturing; manufacturing industry; rough neural network; rough programming scheduling model; rough sets; uncertain information job shop scheduling problem; Decision making; Engineering management; Financial management; Flexible manufacturing systems; Job shop scheduling; Manufacturing industries; Neural networks; Resource management; Rough sets; Uncertainty; Rough Sets; model; neural network; simulation; uncertain information job shop scheduling problem;

fLanguage

English

Publisher

ieee

Conference_Titel

Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on

Conference_Location

Sanya

Print_ISBN

978-1-4244-4247-8

Type

conf

DOI

10.1109/CCCM.2009.5267828

Filename

5267828