(From Wikipedia) The travelling salesman problem, also known as TSP, asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city exactly once and returns to the origin city?" It is an NP-hard problem in combinatorial optimization, important in theoretical computer science and operations research.

During my exploration and analysis of TSP (Traveling Salesman Problem) conundrums, a compelling observation surfaced: it appears that all optimal solutions align with planar graphs. This intriguing revelation piqued my curiosity, prompting me to delve deeper into this phenomenon.

The research can be found at this link. (P31)

In the class on 9th February, our TA delved into the intriguing world of the Traveling Salesman Problem (TSP) using OpenStreetMap, and I must admit, it was quite captivating. The concept of deriving the most efficient route through brute force and nearest neighbor methods to uncover the exact real-world path left me thoroughly fascinated.

What struck me the most was the practical applicability of these methods. The idea that we could apply these algorithms in real-world scenarios, such as tour planning, is incredibly useful. Imagine being able to optimize a journey, whether it's for sightseeing or business, by leveraging these computational tools. It opens up a realm of possibilities for efficiency and precision in planning routes, ultimately saving time and resources.

Moreover, the class not only provided a theoretical understanding but also demonstrated how these methods can be implemented using real data from OpenStreetMap. This hands-on approach not only solidified my understanding but also sparked my curiosity to explore further.

The application can be accessed at this link. (P32)