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
Patty Buchanan,
Assistant Teaching Professsor,
Industrial & Systems Engineering
Students
Daniel Murphy
Danlil Tchistiakov
Drake Foster
Emily Whelan
Trent Wydrowski
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