We developed an algorithm that uses local search and graph optimization to fairly distribute branch territories. The system works with population and geographic data, allows defining custom metrics, and brought the client higher accuracy and network stability.

Assignment

The client needed a tool to fairly and efficiently divide territory among individual branches. The previous third-party method lacked precision and flexibility, resulting in imbalanced branch performance and supply chain issues. The goal was to create a system that ensures equal conditions for sales representatives, balanced branch performance, and stable operation of the entire sales network.

Our Solution

We developed an algorithm for geographic area division that:

• works with a wide range of input data such as population, population density, and geographic location,
• uses an iterative local search algorithm and graph optimization techniques to efficiently find the optimal distribution,
• allows the client to define their own metrics (e.g., population balance, area size, service accessibility) to guide the division,
• provides greater precision, flexibility, and performance compared to the original third-party approach.

Result

Our system enables fair sales territory allocation, unifies conditions for sales representatives, and strengthens network stability. As a result, organizations can achieve higher efficiency and improve collaboration within the supply chain. The project continues to evolve, paving the way for further innovations.

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