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dc.contributor.advisorZech, Wesley
dc.contributor.advisorStroup-Gardiner, Maryen_US
dc.contributor.advisorTurochy, Roden_US
dc.contributor.advisorFulton, Johnen_US
dc.contributor.authorRao, Pradeepen_US
dc.date.accessioned2009-02-23T15:53:11Z
dc.date.available2009-02-23T15:53:11Z
dc.date.issued2007-05-15en_US
dc.identifier.urihttp://hdl.handle.net/10415/1359
dc.description.abstractIn the ready-mix concrete industry, timely and uninterrupted delivery of ready-mix concrete to a construction site is of utmost importance for efficient construction operation. Due to ever soaring fuel prices and small time windows available for the transport of concrete material (i.e. dependent on the concrete setting time) delivering the material using the shortest distance and shortest time is imperative to register profit. For ready-mix concrete batch plant operations to efficiently schedule ready-mix deliveries, reliable assessment of haul travel time from the batch plant to the construction site is critical. However, the dynamic nature of the roadway network owing to constantly changing traffic conditions makes prediction of travel time complicated. Further, the selection of the optimized route can be difficult to identify by utilizing individual cognitive ability. Hence, modern geospatial technologies such as geographic information systems (GIS) and global positioning systems (GPS) are helpful in finding the optimal haul routes. The GIS roadway network and associated traffic data were collected to model the actual roadway network conditions. The GIS roadway network data coupled with traffic information was valuable in identifying optimal haul routes. Time-dependent GIS models were developed to portray the actual traffic conditions on the roadway network for a particular moment in time to calculate a reliable estimation of travel time. GPS data of actual truck haul routes was collected to validate the developed time-dependent GIS models. The time-dependent GIS models developed for actual haul routes exhibited an R2 value of 0.9 in terms of predictive capabilities in determining the actual travel time on the roadway network. The shortest time routes and the shortest distance routes were found for each actual haul route using the developed time-dependent GIS models. The shortest distance models offered a 6.2% savings in distance and shortest time models presented a 16.9% savings in time for haul routes. The savings in haul time will result in higher daily production of the batch plant operation time. The savings in traveled distance could have substantial monetary savings in the long term by reducing the fuel cost associated with the haul operation.en_US
dc.language.isoen_USen_US
dc.rightsEMBARGO_NOT_AUBURNen_US
dc.subjectCivil Engineeringen_US
dc.titleOptimizing Haul Routes Using Geospatial Technologies for the Delivery of Ready-Mix Concrete in Urban Areasen_US
dc.typeThesisen_US
dc.embargo.lengthMONTHS_WITHHELD:24en_US
dc.embargo.statusEMBARGOEDen_US
dc.embargo.enddate2011-02-23en_US


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