Amazon
Multi-Ship Mode Forecasting and Optimization
The student team worked to solve a regional transportation capacity planning problem. The modern fast shipping and supply chain framework has resulted in constant variation in shipping demands. Both short-term and long-term capacity planning require forecasting and optimization solutions. The student team created a tool that can take historical shipper demands as input and generate short term (4-weeks) and long-term (12-months) shipping volume forecast for Full Truckload (FTL), Less-Than-Truckload (LTL) or Small Parcel (SP) carriers. The output of the tool includes intuitive visuals that work for both operators and management teams.
Faculty Adviser(s)
Patty Buchanan, Industrial & Systems Engineering
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