Locating Distribution Centers and Planning Effective Routes for Vaccine Distribution for Low Transportation Costs

Abstract

This paper is a comparative study of the process between the Center of gravity method and the K-means clustering method. Finding distribution centers and routing of Covid-19 vaccines to have low transportation costs, starting from the study of finding vaccine distribution centers into 2 models. Methods of data analysis using the Center of Gravity and data analysis using K-means Clustering. After that, the transportation route will use a genetic algorithm. The genetic algorithm aims to distribute vaccines cost-effectively with the idea that when transport distances are short, transportation costs are reduced. It will be analyzed and compared to finding a distribution center to be able to find shorter distances in transport, which results from the analysis. Compare both methods. The method of data analysis uses the center of gravity. There are 6 vaccine distribution centers and 25 routes for transporting vaccines with a total distance of 8,250 kilometers. The data was analyzed using the K-means clustering method. There were 6 vaccine distribution centers with 26 routes for transporting vaccines with a total distance of 7,501.5 kilometers. The researcher, therefore, chose the effect of K-means Clustering as a guideline for vaccine transport because it can provide a transport route with a shorter total distance for vaccine delivery than the Center of gravity method.