A Decision Support System for Transportation Infrastructure and Supply Chain System Planning
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2013-07-01
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Edition:Final Report
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Abstract:This project makes the results (models and methodology) of the research and development efforts on freight movement modeling (FMM) and supply chain design carried out by faculty at OSU and OU available to transportation and logistics professionals. A web-based DSS called TISCSoft was developed to make the research results available to decision makers in a convenient on-demand format, while providing the researchers a mechanism to keep the models and results current. TISCSoft has been designed to have the look and feel of a typical web-based software. Its home page provides some basic information to all users such as an overview of the DSS project, information about the research team, and links to sponsors and technical/data resources. Access to the DSS functionality is through a login procedure and currently there are three different user groups, namely, Research Team, Planner/Designer and Student. Users belonging to these groups have different access privileges based on their expected need for the various DSS functions. While users belonging to all three groups can analyze freight flows, only users belonging to the Planner/Designer group or the Research Team can access the supply chain network design and user-defined extreme event analysis functions. TISCSoft supports scenario analysis involving either changes in demographic/economic projections or infrastructure changes such as major transportation network disruptions caused by man-made or natural disasters. This is accomplished through a combination of on-line scenario definition and off-line execution of freight flow models. The DSS also implements a novel approach for the design of supply chain networks. The congested travel times on the highway segments provided by the FMM model lead to more realistic transportation costs and times and serve as an input to the supply chain optimizer module. The DSS project also included a case study on the design of a biomass supply chain for switchgrass in western Oklahoma and southwestern Kansas. The supply chain model was extended to include the effect of weather patterns on the allocation and use of land and mechanical resources for a biomass supply chain by employing a scenario optimization approach.
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