Our client, a global shipping company, transports retail goods from East Asian factories to western stores. They aimed to automate and optimize the container assignment process, which previously took days to run and weeks to expand to a new customer.
Our solution involved two key components. Firstly, we trained a machine learning model to predict future shipment volumes based on past data which is crucial for proactive planning. Secondly, we developed a custom algorithm to assign orders to individual containers. This algorithm factored in container availability, shipment origins and destinations, expected arrival dates, and various constraints to optimize container shipment assignments.
1. Cost Savings:
Optimizing assignments and maximizing shipping container efficiency means fewer costs.
2. Improved Efficiency:
Automating container assignments reduces time and resource usage.
3. Clear Path Forward:
An end-to-end robust workflow allows for efficient scenario planning.
Thanks to this project, the client now has an optimization heuristic for decision-making, giving them the flexibility and ease to add new customers as they scale their business.
The Aimpoint Difference
We believe “one size fits all” is a myth when solving your most complex business problems.
We craft custom solutions by prioritizing a business-driven approach. Our team meticulously aligns use cases, KPIs, and tech infrastructure, ensuring a tailored fit to meet specific client needs.
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