Case Study on Vehicle Routing Problem
Artificial Intelligence can be used to improve logistics experience by
increasing reliability, reducing the cost of transportation,
faster processing and deciding best routes.
In real life, route planning has many uncertainties such as changing demands,
traffic accident, or unexpected weather conditions, etc. All of these
uncertainties can lead to more costs in logistics management if not taken to consideration properly.
This is where AI algorithms for optimal Vehicle Routing comes in.
AI is the best assistant for global supply chains in managing assets
and facilities in the most cost-efficient way. The use of AI-based
predictive analytics can help transportation services providers
optimize route planning and delivery schedules. The technology-based
approach ensures improved asset performance due to timely maintenance,
which results in the reduction of cases of failures. To date, the
capabilities of logistics AI solutions seem boundless.
After having AI based algorithm ready, we took the following approach:
PT POS Indonesia provided the list of addresses for delivery of dummy parcels. The Rosebay AI team took the list of those addresses and generated optimal route to deliver the parcels, in addition to that, the normal Team B took a manual route. Both of the team's primary responsibility was to note down the timing information like starting time, destination reaching time, waiting time at destination and traffic time. And the Team A’s individual responsibility was to deliver the parcels by following the route generated by the VRP Algorithm while Team B responsibility was to carry out normal postman delivery.
We were able to achieve tremendous results for this problem with the help of AI.
1. Team A was 27% faster than Team A.
2. Team A saved covered shorter distance than Team B by 33.38 %
3. Team A normalized time by 62.38 % than Team B.