The Shipping Optimization Challenge: A New Data Science Competition

We’ve partnered with CTRL F, a London-based logistics firm, to bring you our biggest competition yet.

Valeriya Kushchuk
bitgrit Data Science Publication
2 min readOct 25, 2020

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We’re excited to announce the newest addition to our AI competition platform: the Shipping Optimization Challenge. We encourage our international data scientist community (where new members are always welcome!) to submit their optimization models to help a client of CTRL F — a logistics firm in London — determine the best way to ship goods.

It’s always challenging for logistics companies to reduce shipping times and costs. Being able to predict these values helps reduce domino-effect delays and improve the overall reliability of deliveries. Finding the best way to ship packages may even help reduce the negative impact of shipping on the environment.

That’s why CTRL F, a global company based in London, partnered with bitgrit to launch this competition. The goal of this competition is to more accurately predict shipping weight, quantities, and delivery time.

Finding the best way to ship packages may even help reduce the negative impact of shipping on the environment.

🚛 Part 1: Forecasting Delivery Time for Shipments

The first dataset contains historical shipment information with known shipping times. Contestants must use the data to train the model and forecast the time required to process each shipment.

The other two parts of the challenge require a time-series forecasting model:

🚛 Part 2: Predicting Shipping Quantities

The second dataset contains historical shipment information over a 16-month period spanning from 2019 to 2020. We’re asking competition participants to create a model that provides a daily forecast of shipment quantities processed over a 2-month period.

🚛 Part 3: Predicting Shipping Weight

The third dataset uses the same information from challenge 2, but asks participants to use this data to create a model that provides a daily forecast of shipment quantity and weight in the 2-month period following the timeframe covered in the dataset.

To qualify for winning a prize, participants need to make a submission for each of the above parts.

The prize breakdown is:

  • 1st place: $4,000
  • 2nd place: $2,500
  • 3rd place: $1,000

The competition started on Oct. 6, 2020, and will end on Nov. 30, 2020 at 8 a.m. UTC. To learn more about the competition and to sign up, head to our website!

Note: This competition is now closed. You can find a list of bitgrit’s other AI competitions on our website here.

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Valeriya Kushchuk
bitgrit Data Science Publication

En-journo from 🇷🇺, now storyteller & social media geek who works with startups in 🇫🇮