Theeyecode/Optimizing-Public-Bus-Network-Scheduling

Developed a Linear Programming model to optimize bus scheduling for Anbessa City Bus Service Enterprise in Addis Ababa, Ethiopia. # 🚌 Optimizing Public Bus Network Scheduling A demand-oriented **Linear & Mixed Integer Programming** model that optimizes urban bus scheduling across routes and time shifts, reducing operational cost while improving service quality. > Operations Analytics Project — University of Niagara Falls (DAMO-610) --- ## 📌 Project Overview Urban public bus systems often operate on fixed schedules that do not reflect real passenger demand. This leads to overcrowding during peak hours, idle buses during off-peak periods, high fuel and maintenance costs, and inconsistent service quality. This project develops a **data-driven optimization framework** to dynamically assign buses across **93 routes and 4 daily shifts**, aligning supply with demand while respecting operational constraints. --- ## 🎯 Objectives - Optimize bus allocation based on passenger demand - Minimize unnecessary trips and distance coverage - Improve fleet utilization during peak and off-peak periods - Maintain acceptable passenger wait times - Support scenario-based planning for demand fluctuations --- ## 🧠 Methodology The problem is formulated as a **Vehicle Scheduling Problem (VSP)** using Linear and Mixed Integer Programming. **Key elements:** - Decision variables represent trips per bus type, route, and shift - Objective function minimizes total trips (proxy for operational cost) - Constraints enforce: - Passenger demand satisfaction - Fleet size and capacity limits - Minimum service frequency - Bus reuse across shifts The model is solved using **SCIP via Google OR-Tools**, enabling efficient handling of complex operational constraints. --- ## 🛠 Tools & Technologies - Python, pywraplp - Google OR-Tools (SCIP Solver) - pandas, NumPy, Matplotlib, math - Jupyter Notebook, Excel - Linear & Mixed Integer Programming --- ## 📊 Key Performance Indicators (KPIs) | Metric | Target | Achieved | |------|------|------| | Operating Cost Reduction | > 10% | **13.74%** | | Distance Coverage Reduct …