Abstract
This paper presents an innovative system architecture development framework that allows the search of optimum architecture solutions within large design space by automating certain model construction, alternative generation, simulation, and assessment tasks. Such framework is facilitated by a holistic modeling approach that combines the capabilities of Object Process Methodology (OPM), Colored Petri Net (CPN) and feature model. the resultant holistic model not only can capture the structural, behavior, and dynamic aspects of a system, allowing strong analysis methods to be applied, but also can specify the architectural design space allowing generation of architecture alternatives that cover it. the proposed framework and suggested implementation is generic targeted at systems that can be specified by logic models using object-oriented paradigm. a partial implementation of the proposed approaches is presented with the design of reconfigurable manufacturing systems (RMSs) as an example, which is formulated as a multi-objective optimization problem with the Genetic Algorithm (GA, particularly, NSGA-2) as the search algorithm. the RMS is a multi-part flow line structure with identical machines in each production stage. © 2012 Published by Elsevier B.V.
Recommended Citation
R. Wang and C. H. Dagli, "Computational System Architecture Development using a Holistic Modeling Approach," Procedia Computer Science, vol. 12, pp. 13 - 20, Elsevier, Jan 2012.
The definitive version is available at https://doi.org/10.1016/j.procs.2012.09.023
Department(s)
Engineering Management and Systems Engineering
Publication Status
Open Access
Keywords and Phrases
Architecture; CPN; Design Space; Feature model; Multi-objective optimization; Object Oriented Modeling; OPM; RMS; Simulation
International Standard Serial Number (ISSN)
1877-0509
Document Type
Article - Conference proceedings
Document Version
Final Version
File Type
text
Language(s)
English
Rights
© 2024 Elsevier, All rights reserved.
Creative Commons Licensing
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Publication Date
01 Jan 2012