The capacitated centered clustering problem (CCCP) involves partitioning a set of n points
on R d (d≥ 2) into p disjoint clusters within a given capacity. Each point has an associated …

This paper introduces an algorithm for solving the minimum sum-of-squares clustering
problems using their difference of convex representations. A non-smooth non-convex …

Clustering is an important task in data mining. It can be formulated as a global optimization
problem which is challenging for existing global optimization techniques even in medium …

The purpose of this paper is to develop new efficient approaches based on DC (Difference
of Convex functions) programming and DCA (DC Algorithm) to perform clustering via …

The aim of this paper is to design an algorithm based on nonsmooth optimization techniques
to solve the minimum sum-of-squares clustering problems in very large data sets. First, the …

In the age of connectivity, every person is constantly producing large amounts of data every
minute: social networks, information about trips, work connections, etc. These data will only …

Clustering is an important problem in data mining. It can be formulated as a nonsmooth,
nonconvex optimization problem. For the most global optimization techniques this problem …

Clustering is one of the most important tasks in data mining. Recent developments in
computer hardware allow us to store in random access memory (RAM) and repeatedly read …

Metaheuristic algorithms have become one of the preferred approaches for solving
optimization problems. Finding the best metaheuristic for a given problem is often difficult …

Este trabalho busca destacar a relevância do tema localização em questões que afetam
diretamente a sociedade moderna, assim como sua relevância no ambiente acadêmico …