The Stanford GraphBase: a platform for combinatorial computing
The Stanford GraphBase: a platform for combinatorial computing
Placing text labels on maps and diagrams
Graphics gems IV
An empirical study of algorithms for point-feature label placement
ACM Transactions on Graphics (TOG)
Tabu Search
A tabu search approach to automated map generalisation
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Labeling Points with Rectangles of Various Shapes
GD '00 Proceedings of the 8th International Symposium on Graph Drawing
On the Design and Analysis of Competent Selecto-recombinative GAs
Evolutionary Computation
Lagrangean relaxation with clusters for point-feature cartographic label placement problems
Computers and Operations Research
Journal of Visual Languages and Computing
A greedy randomized adaptive search procedure for the point-feature cartographic label placement
Computers & Geosciences
Label segregation by remapping stereoscopic depth in far-field augmented reality
ISMAR '08 Proceedings of the 7th IEEE/ACM International Symposium on Mixed and Augmented Reality
Computers and Operations Research
Dispersion for the point-feature cartographic label placement problem
Expert Systems with Applications: An International Journal
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The generation of better label placement configurations in maps is a problem that comes up in automated cartographic production. The objective of a good label placement is to display the geographic position of the features with their corresponding label in a clear and harmonious fashion, following accepted cartographic conventions. In this work, we have approached this problem from a combinatorial optimization point of view, and our research consisted of the evaluation of the tabu search (TS) heuristic applied to cartographic label placement. When compared, in real and random test cases, with techniques such as simulated annealing and genetic algorithm (GA), TS has proven to be an efficient choice, with the best performance in quality. We concluded that TS is a recommended method to solve cartographic label placement problem of point features, due to its simplicity, practicality, efficiency and good performance along with its ability to generate quality solutions in acceptable computational time.