This project implements various algorithms (Dynamic Programming, Backtracking, Greedy, etc.) to solve budget allocation problems modeled as subset sum. Users can manage projects, assign metadata (priority, risk), and get optimal selections within given budgets. Includes visualization and analytics.

Multiple algorithm implementations with performance comparison

Support for time-phased and multi-department budgets

Priority and risk-based weighted selection

Interactive visualization and analytics dashboard

API for integration with other systems

Python (Backend algorithms)

FastAPI (Backend API)

React or Streamlit (Frontend UI)

PostgreSQL (Database)

Docker (Deployment)