I created a Load Board for use in the logistics industry. This application was used by the company with over 100+ office employees and 1000+ drivers to notify and help prioritize company dispatchers of any orders, or loads, that need attention due to being late, or bound to be late. In order to achieve this I had created a back end ETA process that would calculate the ETA of any orders that were currently active.
Below is a video outlining the general use of my Load Board application:
The load board showed a visual graph on how ETA's were calculated by showing the delivery driver's mandated break time, the travel time required to get to the each destination, and the amount of time required to unload/load at each stop, otherwise known as dwell time. The dwell time required to unload/load was calculated via machine learning from historical data.
The second tab of the program also showed any loads that did not have a delivery driver assigned sorted by the date/time the potential driver would need to leave by in order to make an on time delivery for every stop. This information was crucial as it helped prioritize a company dispatcher as to what immediately needed to be worked next.
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