An Optimal Travel Planning Solution Using The Amalgamation of Traveling Salesman Problem and Multiple Linear Regression

With access to various modes of transportation and transport becoming more affordable, travel and tourism have seen a tremendous spike in the years before 2020. We estimate that travel and tourism will surpass their momentum anytime soon in the near future. This project aims towards a planning solution that keeps in mind time and fare. Our project will calculate the shortest distance between each of the user’s chosen locations, as well as the return route, and then recommend the best and most efficient order in which to visit them. This information would also decrease the time it would otherwise take. We will find the most efficient travel and return route in our project through a backtracking solution to Enhanced Travelling Salesman Algorithm. We will further use Multiple Linear Regression to find the cost estimate for this shortest distance. Hence, through our project, we provide users with a complete travel planning solution that considers time, distance, and fare.