The Point-Feature Cartographic Label Placement (PFCLP) problem consists of placing text labels to point
features on a map avoiding overlaps to improve map visualization. This paper presents a Clustering
Search (CS) metaheuristic as a new alternative to solve the PFCLP problem. Computational experiments
were performed over sets of instances with up to 13,206 points. These instances are the same used in sev-
eral recent and important researches about the PFCLP problem. The results enhance the potential of CS by
finding optimal solutions (proven in previous works) and improving the best-known solutions for
instances whose optimal solutions are unknown so far.
