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I work on building an Automatic Inventory Allocation System that helps replace manual

tribution decisions in supply chain operations. The main problem is that inventory allocation

usually done manually based on experience, sales history, and intuition. This process is slow,

d to scale, and often leads to issues like stockouts, overstocking, lost sales, and conflicts

ween branches.

The system uses historical sales data, demand patterns, and business constraints to decide:

ow much of each product should be sent to each branch.

ow frequently branches should be replenished.

nd how to balance service level, cost, and fairness.

We assume that the data is collected from public or secondary sources, and the solution is designed to be flexible and realistic, even if the exact company schema is not available yet.

The final goal is to improve service level, reduce lead time, and increase revenue by making inventory flow faster and more balanced across the network.

Phases We Will Follow:

- Environment Setup, Reproducibility

- Schema Validation

- Initial Data Inspection

- Data Quality, Consistency Checks

- Data Cleaning, Fixing

- Data Enhancement, Feature Engineering

- Data Reduction, Modeling Readiness

- Allocation Logic Design

- Transport Cost Calculation

- Calculate Total Order Cost

- Allocation Performance Metrics

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