Board 102 : Truck-Drone Two-tier Delivery Network Design

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dc.contributor.author Erdem, Ergin
dc.contributor.author Johson, Christopher
dc.contributor.author shim, Sang Ho
dc.contributor.author Williams, Jordan
dc.date.accessioned 2020-03-30T17:04:21Z
dc.date.available 2020-03-30T17:04:21Z
dc.date.issued 2018-06
dc.identifier.citation Erdem, E., & Johnson, C., & Shim, S., & Williams, J. (2018, June), Board 102 : Truck-Drone Two-tier Delivery Network Design Paper presented at 2018 ASEE Annual Conference & Exposition , Salt Lake City, Utah. https://peer.asee.org/29859 en_US
dc.identifier.uri http://hdl.handle.net/11347/353
dc.description.abstract We develop case study materials for the future of supply chain logistics; Truck-Drone two tier delivery network design. FedEx Headquarter (HQ) in a city was used as the networks root node or central distribution center (DC). FedEx Office locations were chosen as potential drone distribution facilities. Three locations were used but the model was developed to make drone facility additions as needed. We chose major zip-code areas supported by the HQ to use as drone drop off locations with zip-code populations serving as product demand. Ten zip-codes were chosen, but this number can also be fluctuated as needed in the truck-drone model. In a depiction of the truck-drone model with FedEx HQ as the root node, linehaul to drone facility is the first arc and drone facility to destination as the second arc. Two methods were used to capture distance along network arcs. Linehaul distance from HQ to drone facility was found using Google Map technology. This technology provided best highway route, mileage, and time determination for truck travel, as well as longitude and latitude information. After longitude and latitude coordinates were determined, Haversine’s Formula, which calculates distance between points on spheres, was used to calculate distance between drone facilities and zip-code destinations. An independent Worksheet of assumptions is made for future use in more realistic assumptions. The main Worksheet invoke the input data from the Worksheet of assumptions. After all data concerning the network model was established and fixed and variable costs were estimated, the next step was to model the truck-drone delivery network in Excel and utilize the software’s solver capabilities for optimal route generation. Excel provided sufficient functionality needed to develop the truck-drone model; the platform can handle the Linear Programming formulation used over the truck-drone model and using Excel allows the formulation to be understood at novice and expert levels. Column-row functionality provided by Excel also allows the truck-drone model to have dynamic features. Drone facilities and zip-code or destinations can be added or subtracted as desired. The initial Excel Worksheet is designed by an undergraduate senior student taking an undergraduate research course in Spring 2017. Using Excel Solver an add-in to Micro Soft Excel, the student solved the problem to select drone distribution facilities among 3 possible locations. His Worksheet is being refined by other students taking a Supply Chain Engineering course as course project in Fall 2017. To increase the scale of the problem including a realistic scale of 10 or more potential locations in a city, they use Open Solver another add-in to Micro Soft Excel which is endorsed by Computational Infrastructure for Operations Research (COIN-OR.) en_US
dc.language.iso en_US en_US
dc.publisher ASEE en_US
dc.title Board 102 : Truck-Drone Two-tier Delivery Network Design en_US
dc.type Presentation en_US


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