A Tabu Search Algorithm for the Capacitated Centred Clustering Problem

The capacitated centered clustering problem CCCP consists in partitioning a set of n points in < in p disjoint clusters within a given capacity. Each point has an associated demand and the objective is to minimize the sum of the Euclidean distances between the points and the their respective clusters centroids. In this work, we address the CCCP and also its variant, the g-CCCP, which unleashes the number of clusters p and establishes the opening cost of clusters F . We propose effective strategies that combined with the classical Tabu Search metaheuristic outperform the recent methods published.