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Ontologies for supply chain simulation modeling
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Source Winter Simulation Conference archive
Proceedings of the 37th conference on Winter simulation table of contents
Orlando, Florida
SESSION: Ontologies in simulation: ontologies in simulation table of contents
Pages: 2364 - 2370  
Year of Publication: 2005
ISBN:0-7803-9519-0
Authors
Mohamed Fayez  University of Central Florida, Orlando, FL
Luis Rabelo  University of Central Florida, Orlando, FL
Mansooreh Mollaghasemi  University of Central Florida, Orlando, FL
Publisher
Winter Simulation Conference 
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ABSTRACT

Simulation might be an effective decision support tool in supply chain management. The review of supply chain simulation modeling methodologies revealed some issues one of which is the practicability of simulation in the supply chain environment. The supply chain environment is dynamic, information intensive, geographically dispersed, and heterogeneous. In order to develop usable supply chain simulation models, the models should be feasibly applicable in the supply chain environment. Distributed simulation models have been used by several researchers, however, their complexity and usability hindered their continuation. In this paper, a new approach is proposed. The approach is based on Ontologies to integrate several supply chain views and models, which captures the required distributed knowledge to build simulation models. The Ontology core is based on the SCOR model as the widely shared supply chain concepts. The ontology can define any supply chain and help the user to build the required simulation models.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Berners-Lee, T. 1998. Semantic Web Roadmap, from <http://www.w3.org/DesignIssues/Semantic.html>
 
2
Fayez, M., Axelsson, P., & Hosni, Y. 2003. Information intensive projects: planning and optimizing using the Design Structure Matrix (DSM). Paper presented at the 2003 Industrial Engineering annual conference, Portland, Oregon.
 
3
Huang, G. Q., Lau, J. S. K., & Mak., K. L. 2003. The Impacts of Sharing Production Information on Supply Chain Dynamics: a review of the literature. International Journal of Production Research, 41(7), 1483--1517.
 
4
KBSI. 2003. Integrated DEFinition methods IDEF. from <http://www.kbsi.com>
 
5
Motwani, J., Madan, M., & Gunasekaran, A. 2000. Information technology in managing global supply chains. Logistics Information Management, 13(5), 320--327.
 
6
OMG. Unified Modeling Language (UML). <http://www.uml.org>
 
7
Prasad, S., & Tata, J. 2000. Information investment in supply chain management. Logistics Information Management, 13(1), 33--38.
 
8
SCC. 2003. Supply Chain Operations Reference (SCOR) Model V.6.0.
 
9
Swaminathan, J. M., Sadeh, N. M., & Smith, S. F. 1997. Effect of sharing supplier capacity information. Haas School of Business, University of California, Berkeley.
 
10
Thonemann, U. W. 2002. Improving supply chain performance by sharing advance demand information. European Journal of Operational Research, 142(1), 81--107.
 
11
W3C. (2003a). Resource Description Framework (RDF), from <http://www.w3.org/RDF>
 
12
W3C. (2003b). World Wide Web Consortium- Semantic Web. Retrieved 2003
 
13
Yu, Z., Yan, H., & Cheng, T. C. E. 2001. Benefits of information sharing with supply chain partnerships. Industrial Management, 101(3), 114--121.
 
14
Zhao, X., Xie, J., & Zhang, W. J. 2002. The impact of information sharing and ordering co-ordination on supply chain performance. Supply Chain Management: An International Journal, 7(1), 24--40.
Collaborative Colleagues:
Mohamed Fayez: colleagues
Luis Rabelo: colleagues
Mansooreh Mollaghasemi: colleagues