Optimal labelling of point features in the slider model

Abstract

We investigate the label number maximisation problem (LNM): Given a set of labels, each of which belongs to a point feature in the plane, the task is to nd a largest subset ∧P of ∧so that each λ ∈P labels the corresponding point feature and no two labels from ∧P 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 signicantly higher number of labels that can be placed. To our knowledge, we present the rst 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.