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A Clustering Search metaheuristic for the Point-Feature Cartographic Label Placement Problem

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  • Rabello, Rômulo Louzada
  • Mauri, Geraldo Regis
  • Ribeiro, Glaydston Mattos
  • Lorena, Luiz Antonio Nogueira

Abstract

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 several 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.

Suggested Citation

  • Rabello, Rômulo Louzada & Mauri, Geraldo Regis & Ribeiro, Glaydston Mattos & Lorena, Luiz Antonio Nogueira, 2014. "A Clustering Search metaheuristic for the Point-Feature Cartographic Label Placement Problem," European Journal of Operational Research, Elsevier, vol. 234(3), pages 802-808.
  • Handle: RePEc:eee:ejores:v:234:y:2014:i:3:p:802-808
    DOI: 10.1016/j.ejor.2013.10.021
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    References listed on IDEAS

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    1. Alvim, Adriana C.F. & Taillard, Éric D., 2009. "POPMUSIC for the point feature label placement problem," European Journal of Operational Research, Elsevier, vol. 192(2), pages 396-413, January.
    2. Ribeiro, Glaydston Mattos & Laporte, Gilbert & Mauri, Geraldo Regis, 2012. "A comparison of three metaheuristics for the workover rig routing problem," European Journal of Operational Research, Elsevier, vol. 220(1), pages 28-36.
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    Cited by:

    1. Karmitsa, Napsu & Bagirov, Adil M. & Taheri, Sona, 2017. "New diagonal bundle method for clustering problems in large data sets," European Journal of Operational Research, Elsevier, vol. 263(2), pages 367-379.

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