An empirical study of algorithms for point-feature label placement
ACM Transactions on Graphics (TOG)
Point labeling with sliding labels
Computational Geometry: Theory and Applications - Special issue on applications and challenges
LEDA: a platform for combinatorial and geometric computing
LEDA: a platform for combinatorial and geometric computing
Optimal Compaction of Orthogonal Grid Drawings
Proceedings of the 7th International IPCO Conference on Integer Programming and Combinatorial Optimization
Negative-Cycle Detection Algorithms
ESA '96 Proceedings of the Fourth Annual European Symposium on Algorithms
An Optimisation Algorithm for Maximum Independent Set with Applications in Map Labelling
ESA '99 Proceedings of the 7th Annual European Symposium on Algorithms
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We investigate the label number maximisation problem (LNM): Given a set of labels Λ, each of which belongs to a point feature in the plane, the task is to find a largest subset ΛP of Λ so that each λ ∈ ΛP labels the corresponding point feature and no two labels from ΛP overlap. Our approach is based on two so-called constraint graphs, which code horizontal and vertical positioning relations. The key idea is to link the two graphs by a set of additional constraints, thus characterising all feasible solutions of LNM. This enables us to formulate a zero-one integer linear program whose solution leads to an optimal labelling. We can express LNM in both the discrete and the slider labelling model. The slider model allows a continuous movement of a label around its point feature, leading to a significantly higher number of labels that can be placed. To our knowledge, we present the first algorithm that computes provably optimal solutions in the slider model. First experimental results on instances created by a widely used benchmark generator indicate that the new approach is applicable in practice.