Title
Multivariate regression metamodel: a DSS application in industry
Abstract
A materials handling system simulation (written using GPSS/H) was developed, to predict the Automated Guided Vehicle requirements necessary for a major manufacturer to maintain desired levels of production in one of its automobile assembly plants. Rather than use the simulation as a representational DSS and risk complicating the user interface, validated simulation outputs were collected and used to produce a multivariate regression metamodel. This metamodel formed the centerpiece of a narrow-scope suggestion model DSS used on the factory floor to aid in day to day allocations of resources. This article looks at the metamodel development methodology and offers this technique as an effective means of producing a suggestion model DSS from a more complex representational DSS.
Year
DOI
Venue
1997
10.1016/S0167-9236(96)00037-1
Decision Support Systems
Keywords
Field
DocType
computer simulation,multivariate regression,metamodel,decision support system
Data mining,Automated guided vehicle,Software engineering,Computer science,Expert system,Decision support system,GPSS,Artificial intelligence,Knowledge base,Systems architecture,User interface,Metamodeling
Journal
Volume
Issue
ISSN
19
1
0167-9236
Citations 
PageRank 
References 
7
0.70
9
Authors
2
Name
Order
Citations
PageRank
Roger McHaney111617.47
David E. Douglas2737.86