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AUTOMATIC GENERATION OF SUPPLY CHAIN SIMULATION MODELS FROM SCOR BASED ONTOLOGIES

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Date Issued:
2008
Abstract/Description:
In today's economy of global markets, supply chain networks, supplier/customer relationship management and intense competition; decision makers are faced with a need to perform decision making using tools that do not accommodate the nature of the changing market. This research focuses on developing a methodology that addresses this need. The developed methodology provides supply chain decision makers with a tool to perform efficient decision making in stochastic, dynamic and distributed supply chain environments. The integrated methodology allows for informed decision making in a fast, sharable and easy to use format. The methodology was implemented by developing a stand alone tool that allows users to define a supply chain simulation model using SCOR based ontologies. The ontology includes the supply chain knowledge and the knowledge required to build a simulation model of the supply chain system. A simulation model is generated automatically from the ontology to provide the flexibility to model at various levels of details changing the model structure on the fly. The methodology implementation is demonstrated and evaluated through a retail oriented case study. When comparing the implementation using the developed methodology vs. a "traditional" simulation methodology approach, a significant reduction in definition and execution time was observed.
Title: AUTOMATIC GENERATION OF SUPPLY CHAIN SIMULATION MODELS FROM SCOR BASED ONTOLOGIES.
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Name(s): Cope, Dayana , Author
Sepulveda, Jose, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2008
Publisher: University of Central Florida
Language(s): English
Abstract/Description: In today's economy of global markets, supply chain networks, supplier/customer relationship management and intense competition; decision makers are faced with a need to perform decision making using tools that do not accommodate the nature of the changing market. This research focuses on developing a methodology that addresses this need. The developed methodology provides supply chain decision makers with a tool to perform efficient decision making in stochastic, dynamic and distributed supply chain environments. The integrated methodology allows for informed decision making in a fast, sharable and easy to use format. The methodology was implemented by developing a stand alone tool that allows users to define a supply chain simulation model using SCOR based ontologies. The ontology includes the supply chain knowledge and the knowledge required to build a simulation model of the supply chain system. A simulation model is generated automatically from the ontology to provide the flexibility to model at various levels of details changing the model structure on the fly. The methodology implementation is demonstrated and evaluated through a retail oriented case study. When comparing the implementation using the developed methodology vs. a "traditional" simulation methodology approach, a significant reduction in definition and execution time was observed.
Identifier: CFE0002009 (IID), ucf:47625 (fedora)
Note(s): 2008-05-01
Ph.D.
Engineering and Computer Science, Department of Industrial Engineering and Management Systems
Doctorate
This record was generated from author submitted information.
Subject(s): Ontology
Simulation Modeling and Analysis
Supply Chain Systems
SCOR Model
Logistics
Automatic Generation Simulation
Decision Making Tool
Supply Chain Modeling
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0002009
Restrictions on Access: public
Host Institution: UCF

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