Smart City Route Optimization System

A graph-based route optimization system implemented in C++, designed to compute the shortest path between city locations. This project models real-world road networks as weighted graphs and applies Dijkstra’s Algorithm with priority queues for efficient pathfinding.

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🚦 Project Overview

Modern smart cities rely on efficient routing for navigation, logistics, and emergency response. This project simulates a city road network where:

• Locations are represented as nodes
• Roads are represented as weighted edges (distance/cost)

The system computes the shortest route and total distance between a source and destination node using an optimized graph algorithm.

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🎯 Key Features

• Graph representation using adjacency lists
• Efficient shortest-path computation using Dijkstra’s Algorithm
• Priority queue–based optimization for faster performance
• Outputs both minimum distance and actual route path
• Command-line driven input for flexibility

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🧠 Algorithm Used

Dijkstra’s Algorithm

• Greedy shortest-path algorithm
• Suitable for weighted graphs with non-negative edge weights
• Time complexity optimized using a min-heap (priority queue)

This makes it ideal for modeling real-world city road networks.

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🏗️ System Design

• Data Structure:

  • unordered_map<string, vector<pair<string, int>>> for adjacency list

• Nodes: City locations (e.g., A, B, C, D)

• Edges: Roads with distance as weight

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📁 Project Structure

Smart-City-Route-Optimization/
│
├── main.cpp      # Complete implementation
├── README.md

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▶️ How to Compile and Run

1️⃣ Compile

g++ main.cpp -o route_optimizer

2️⃣ Run

./route_optimizer A D

3️⃣ Sample Output

Distance: 3
Path: A -> C -> D

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🔢 Example Graph Used

The sample city map includes:

• A ↔ B (4)
• A ↔ C (2)
• B ↔ D (5)
• C ↔ D (1)

This demonstrates how the system chooses the optimal path instead of the shortest hop count.

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💡 Real-World Applications

• Smart city navigation systems
• GPS and mapping services
• Logistics and delivery route planning
• Emergency vehicle routing

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🚀 Future Enhancements

• Support for directed graphs (one-way roads)
• Dynamic traffic-based edge weights
• Integration with real map data
• Visualization of routes

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👤 Author

Utsav Kashyap data Scientist C++ | Data Structures | Algorithms

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