ISSN 2079-3537      

 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                                                                                             

Scientific Visualization, 2022, volume 14, number 2, pages 27 - 35, DOI: 10.26583/sv.14.2.03

Automating Placement of Point Feature Labels on a Digital Map using Non-linear Mathematical Programming

Authors: M. Y. Zarubin1,A,B, I. G. Pristupa2,B, S. V. Ktitrov3,A

A National Research Nuclear University MEPhI, Moscow, Russia

B JSC «Concern «Sozvezdie», Voronezh, Russia

1 ORCID: 0000-0003-0104-6871, Zarubin.Misha@gmail.com

2 ORCID: 0000-0002-8985-8358, inna.g.pristupa@yandex.ru

3 ORCID: 0000-0002-7963-9151, svktitrov@mephi.ru

 

Abstract

A paper considers one of the approaches to solving the problem of automating placement of point feature labels on a digital map. The causes of label overlaps are analyzed, and requirements for label placement are formulated. Two different statements of optimization problems are proposed for finding the optimal locations of labels of point feature labels on a digital map. One of them is based on the idea that as the distance between labels increases, the chance of labels overlay decreases, and as a result, it becomes possible to identify each point feature on a digital map and read information about it presented on the label. In another statement, it is proposed to minimize the distances from objects to their labels in order to quickly and efficiently identify a particular object on the map. The article presents the results of solving optimization problems, which show the fundamental possibility of obtaining optimal label locations and demonstrates the quality of label placement using the considered approaches.

 

Keywords: digital map, label, optimization methods, optimization problem, labels overlay.