This Java project utilizes the K-means clustering algorithm to find the optimal placement of processing plants across Europe. The primary objective is to minimize the distance between waste accumulation sites (garbage collection facilities) and processing plants, enhancing the efficiency of waste management.
In Europe, various locations serve as garbage collection facilities, each with a specific annual capacity measured in tonnes. This capacity represents the amount of waste accumulated annually at each site. The project aims to determine the sub-optimal placement of a given number of processing plants to efficiently process this accumulated waste.
K-means clustering is a fundamental algorithm in the field of clustering. It segregates a given dataset into a specified number (k) of clusters, optimizing the intra-cluster variance. In this project, the algorithm is tailored to handle GPS coordinates of locations in Europe, clustering them based on their proximity and capacity for waste accumulation.
