This project is built for an academic project exhibition with the community in mind.
The project is built based on the concept of the Travelling Salesman Problem. We are making our project to optimize the travel path taken by Covid personnel for visiting various houses in a locality. We have implemented Genetic Algorithm to find the optimum path solution and then have displayed the output as an HTML file which displays the map of the locality and traces the path to be taken for visiting the houses. The visiting sequence is also altered based on the rank given to the houses as per the comfortable visit time.
For implementing the GA a population of 500 house visit order is considered and a fitness score is assigned to all the members of the population as per their travel distance for that particular order. A new generation is then created, with the fitness score in consideration, at random with the population members' having better fitness sore to have higher chances at being in the mating pool for creating a new population. A mutations of a certain rate are also caused to happen while making new generations to aid our aim of finding an optimum solution to our problem. This process is continued for 100 generations. Then for another 100 generations, the program is executed to check if any change occurs in the all-time best solution obtained from the past 100 generations. If there is no change in the all-time best solution, then consider this all-time best solution to be the truly most optimum solution for our considered dataset, else we repeat the process for the next 100 generations till our goal of no change in optimum route over 100 generations is obtained.
We were able to make this project only because of the guidance provided by Dr. Rakesh R., a professor of VIT, Bhopal(at present).
Sources used for this project are the video tutorial series of
both from The coding train.