Graph-Search-Algorithms-Visualization

This project is a Python-based GUI application built using PyQt6 and NetworkX to visualize and compare various graph search algorithms.

It allows users to select a start and end node in a predefined graph and run different search algorithms to find the shortest path. The program also displays the path, execution time, and the number of nodes explored for each algorithm.

Features

Graph Representation:

The graph represents a supermarket layout, with nodes as sections (e.g., "Entrance", "Fruits", "Dairy") and edges as paths between sections with associated weights.

The graph is predefined and visualized using NetworkX and Matplotlib.

Search Algorithms:

• BFS (Breadth-First Search)

• DFS (Depth-First Search)

• Dijkstra's Algorithm

• A* Search

• UCS (Uniform Cost Search)

• DLS (Depth-Limited Search)

• IDS (Iterative Deepening Search)

• BDS (Bidirectional Search)

GUI Features:

• Dropdown menus to select the start and end nodes.

• A table to display the results of each algorithm, including:

  • Algorithm name

  • Path found

  • Execution time

  • Number of nodes explored

• A graph visualization that highlights the path found by the selected algorithm.

Requirements

To run this program, you need the following Python libraries installed:

• PyQt6: For the graphical user interface.

• NetworkX: For graph creation and manipulation.

• Matplotlib: For graph visualization.

Code Structure

Graph Definition:

The graph is defined using NetworkX with weighted edges representing the supermarket layout.

Search Algorithms:

BFS, DFS, Dijkstra, and A* are implemented using NetworkX functions.

UCS, DLS, IDS, and BDS are implemented as custom algorithms.

GUI:

The GUI is built using PyQt6 and includes:

• A QTableWidget to display results.

• A FigureCanvas to visualize the graph.

• Dropdown menus and buttons for user interaction.