Aegisrockers - AI power delivery route optimisation - Deep Tech or Machine Learning

[veeramanikandansrm]

Aegisrockers - AI power delivery route optimisation - Deep Tech or Machine Learning

ℹ️ Project information

1. Deep Tech/Machine Learning (Theme is sponsored by UNILEVER and has 3 Problem Statements) Problem Statement 2 - Route Optimization and Visualization for Sales Vehicles

2. AI power delivery route optimisation: advanced delivery solutions for retail supply chain

3. AI powered Forecasting for sale of each item in all store and VRPTW based route optimization

4. Aegisrockers:

5. Team Members: Veeramanikandan (https://github.com/veeramanikandansrm), Ankur, Promod Krishana, Praveen

6. Demo Link: Please check the coding uploaded here https://github.com/veeramanikandansrm/aegisrockers

7. Repository Link(s): https://github.com/veeramanikandansrm/aegisrockers

8. Presentation Link: https://github.com/veeramanikandansrm/aegisrockers/blob/master/Route%20Optimization%20and%20Visualization%20for%20Sales%20Vehicles.pdf.

9. Deep Tech - Problem Statement - 3: If you have chosen to work on the problem statement - 3 then please submit both models based on the two datasets provided to you. https://www.kaggle.com/c/competitive-data-science-predict-future-sales/data

🔥 Your Pitch

• Forcast the need of each client on a weekly bases and aggregate the total need of each store.
• Machine Learning Model will be used for this forecasting
• Vehicle Routing Problem with Time Windows (VRPTW) for developing this item to the stores with constraints like a number of vehicles, vehicle Capacity and operation cost.
• Based on the demand and vehicles availability the optimized route us calculated using VRPTW as per https://doi.org/10.1016/j.jksus.2010.03.002
• Plot the optimized route for each vehicle on the google map
• Total operation cost and the optimized route is displayed in the dashboard

🔦 Any other specific thing you want to highlight?

• AI-powered demand-based on-time supply with route optimization

✅ Checklist

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