Optimization algorithms with adaptive learning for logistic planning

Abstract

With the rise in popularity of Artificial Intelligence (AI) over the years, it has become more important than ever to capitalise on this interest to not only educate those who are interested, but also to inspire them to develop this interest into a skill. However, without knowledge of coding, it is difficult for people to learn about AI effectively. This project aims to address this issue by aiming to solve a popular computational problem called the Traveling Salesman Problem (TSP), which is an abstract representation of general logistic planning issues. By introducing a holistic package, which includes building hardware (Arduino based, wirelessly-controlled vehicle) and coding software for beginners, and by choosing materials which are easily available and accessible, both online and offline, it ensures that the barrier to entry is kept low to maximise the interest of learners. At the end of the program, learners would get to demonstrate their knowledge by showcasing their vehicle and code to solve a logistic planning scenario.