Problem Statement
The aim of this project is to design a program that utilizes randomized algorithms to solve the train rescheduling problem. This problem considers distance and time as random variables while keeping other variables constant.
Algorithms Used
The given code implements the following algorithms:
Kruskal's Algorithm with Randomized Edge Selection: Kruskal's algorithm is a minimum-spanning-tree algorithm that finds an edge of the least possible weight that connects any two trees in the forest. In this implementation, edge selection is randomized, adding an element of randomness to the algorithm.
Dijkstra's Algorithm: Dijkstra's algorithm is used to find the shortest path between two nodes in a graph. It traverses the graph in a greedy manner, always choosing the vertex with the smallest distance from the source vertex.
Approach
We solved the proposed train rescheduling problem using a randomized algorithm, incorporating both Kruskal's and Dijkstra's algorithms. These algorithms help in finding optimal solutions while considering distance and time as random variables.
Usage
The program provided can be used to solve train rescheduling problems. Users can input necessary parameters and execute the algorithms to obtain solutions.
Note
Ensure that all dependencies and libraries required by the program are installed before execution. Refer to the program documentation for further details on usage and setup. This project demonstrates the practical application of randomized algorithms in solving real-world problems, specifically in the context of train rescheduling.