Neural and heuristic job allocation planner for AGVs

Author

Bostel, A.J. ; Gan, W.W. ; Sagar, V.K. ; See, C.H.

Author_Institution

Dept. of Electron. Syst. Eng., Essex Univ., Colchester, UK

fYear

1993

fDate

1-3 Dec 1993

Firstpage

30

Lastpage

35

Abstract

Automated guided vehicles (AGVs) are automatic load carriers that transfer objects from one location to another in a factory environment. Due to the increasing complexity of factory floor environments coupled with the need for increased flexibility in AGV systems, it is becoming increasingly important to be able to dynamically alter both the AGV job queue and the AGV path. In this paper, a new method based on an artificial neural network model is presented for evaluating the best job assignment so as to achieve better system efficiency

Keywords

automatic guided vehicles; neural nets; planning (artificial intelligence); scheduling; AGV job queue; AGV path; AGVs; artificial neural network model; automated guided vehicles; automatic load carriers; factory environment; job assignment; neural heuristic job allocation planner; Artificial neural networks; Automotive engineering; Computer architecture; Gallium nitride; Navigation; Operations research; Production facilities; Systems engineering and theory; Traffic control; Vehicles;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Fuzzy Control and Intelligent Systems, 1993., IFIS '93., Third International Conference on

Conference_Location

Houston, TX

Print_ISBN

0-7803-1485-9

Type

conf

DOI

10.1109/IFIS.1993.324219

Filename

324219