TSP_Data_Analysis

Traveling Salesman Problem Data Analysis using Python In our project required data were multiple number of cities as instances and their GPS coordinate values. Instances and the values were used to calculate the distance value. In order to comment on the program based on the TSP solution we definitely need separate exact GPS values otherwise one missing coordinate may result wrong on our solution. In order to use step by step project building we have used iPython notebook for implementation of our project. The benefits for using the iPython notebook also known as the Jupyter notebook were that they were easy to be saved and continued later by our group members since the notebook provides an accessible interactive coding via internet. In addition to that parts we have created in the project such as data preparation, modelling and visualization were divided into parts by headings to be coded visually better and to make the code more understandable. Finally, in order to collect our need data from the website we had needed to use Jupyter which provides interactive computing beside that Anaconda Navigator, a desktop graphical user interface helped as to get the required packages such as folium and gurobi easily with its conda packages, environments and channels.