This project implements a solution to a computationally challenging problem involving the calculation of the maximum possible summation of integers from a matrix of arbitrary dimensions. The solution utilizes advanced concepts from graph theory and programming to achieve the desired outcome.
This repository contains the implementation of a graph structure and algorithms in C, developed as part of my Advanced Data Structures class at Instituto Politécnico do Cávado e do Ave. The focus is on implementing and manipulating graphs using advanced concepts in graph theory and programming in C.
The generate-random-graph.py file can be used to generate any sized graph in a CSV format to test the program.
- Graph structure using hash tables and linked lists for efficient memory usage and performance.
- Support for reading and writing graphs from/to CSV and binary files.
- Implemented algorithms include Dijkstra's algorithm for shortest path, Depth-First Search (DFS), and algorithms to find maximum paths.
The CSV file format for graph input should follow this structure:
1;2;3;3;2
2;1;2;3;5
3;1;7
Where each line represents a vertex followed by its adjacent vertices and weights.
The project supports reading and writing graphs in binary format. Use the provided functions to save and load graphs.
The DFS algorithm is used to explore all vertices and edges of the graph to calculate the path with the maximum weight.
Dijkstra's algorithm is used to find the shortest path between vertices in a weighted graph.
The algorithm to find the maximum path uses a modified version of Dijkstra's algorithm to compute the longest path between vertices.
All documentation for this project is available inside the Docs folder.