Developing An Intelligent Logistics and Distribution System For A Large Number of Retail Outlets: A Big Data Analytics Approach

The logistics and distribution system in the retail industry in Indonesia has its own complexity. The growth and productivity of the retail outlets in Indonesia have been increasing from year to year. Distribution activities in this study are related to the formation of salesman visit routes involving around 38,900 customer base retail outlets, which are quite numerous in number, calling for a challenging approach to find the optimized solution. Therefore, the case study in this research will be discussed on the concept of the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), considering the work balance and visit pattern constraints. The methods used in this research are the balanced K-means and the Minimum Span Tree – Kruskal’s Walk algorithm, which are proven to solve the problem with a shorter computation time and a more balanced daily route than the current conditions as the results.