Abstract
A framework for aiding the construction of simulation models in system design problems is presented. The framework employs concepts of artificial intelligence and simulation modeling. A knowledge representation scheme called system entity structure expresses information about the structure of the system to be designed and its corresponding models. More specifically, the entity structure represents objects and their attributes, decompositions, and taxonomies. A knowledge base of production rules is defined for a given design domain and is incorporated in an expert system shell which recommends a feasible configuration of design objects from the system entity structure, based on specific design objectives, constraints, and requirements. This configuration is a basis for constructing a model of the system. The methodology for constructing the system entity structure and its corresponding rule base is presented. A case study based on a high level robot design problem is discussed to illustrate the conceptual framework.
| Original language | English |
|---|---|
| Pages (from-to) | 330-344 |
| Number of pages | 15 |
| Journal | ORSA journal on computing |
| Volume | 3 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 1991 Jan 1 |
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All Science Journal Classification (ASJC) codes
- Engineering(all)
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Rule-based generation of model structures in multifaceted modeling and system design. / Rozenblit, Jerzy W.; Huang, Yueh-Min.
In: ORSA journal on computing, Vol. 3, No. 4, 01.01.1991, p. 330-344.Research output: Contribution to journal › Article
TY - JOUR
T1 - Rule-based generation of model structures in multifaceted modeling and system design
AU - Rozenblit, Jerzy W.
AU - Huang, Yueh-Min
PY - 1991/1/1
Y1 - 1991/1/1
N2 - A framework for aiding the construction of simulation models in system design problems is presented. The framework employs concepts of artificial intelligence and simulation modeling. A knowledge representation scheme called system entity structure expresses information about the structure of the system to be designed and its corresponding models. More specifically, the entity structure represents objects and their attributes, decompositions, and taxonomies. A knowledge base of production rules is defined for a given design domain and is incorporated in an expert system shell which recommends a feasible configuration of design objects from the system entity structure, based on specific design objectives, constraints, and requirements. This configuration is a basis for constructing a model of the system. The methodology for constructing the system entity structure and its corresponding rule base is presented. A case study based on a high level robot design problem is discussed to illustrate the conceptual framework.
AB - A framework for aiding the construction of simulation models in system design problems is presented. The framework employs concepts of artificial intelligence and simulation modeling. A knowledge representation scheme called system entity structure expresses information about the structure of the system to be designed and its corresponding models. More specifically, the entity structure represents objects and their attributes, decompositions, and taxonomies. A knowledge base of production rules is defined for a given design domain and is incorporated in an expert system shell which recommends a feasible configuration of design objects from the system entity structure, based on specific design objectives, constraints, and requirements. This configuration is a basis for constructing a model of the system. The methodology for constructing the system entity structure and its corresponding rule base is presented. A case study based on a high level robot design problem is discussed to illustrate the conceptual framework.
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UR - http://www.scopus.com/inward/citedby.url?scp=0026225694&partnerID=8YFLogxK
U2 - 10.1287/ijoc.3.4.330
DO - 10.1287/ijoc.3.4.330
M3 - Article
VL - 3
SP - 330
EP - 344
JO - INFORMS Journal on Computing
JF - INFORMS Journal on Computing
SN - 1091-9856
IS - 4
ER -