Balance algorithm for point-feature label placement problem

Authors:
Zheng He;Koichi Harada
Affiliations:
Graduate School of Engineering, Hiroshima University, Japan;Department of Integrated Arts & Sciences, Hiroshima University, Japan
Venue:
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
Year:
2005

Citing 6
Cited 0

A Prolog rule-based system for cartographic name placement

Computer Graphics Forum
The solution of large 0–1 integer programming problems encountered in automated cartography

Operations Research
Placing text labels on maps and diagrams

Graphics gems IV
Mapping combinatorial optimization problems onto neural networks

Information Sciences—Intelligent Systems: An International Journal
An empirical study of algorithms for point-feature label placement

ACM Transactions on Graphics (TOG)
Limitations of neural networks for solving traveling salesman problems

IEEE Transactions on Neural Networks

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes an improved discrete Hopfield Neural (HN) network, balance algorithm, to optimize the Point-Feature Labeling Placement (PFLP) problem. The balance algorithm attains the balance between penalty function and original objective function based on the principle of weight balance, and can converge to the solution with better stability. This improved algorithm also allows HN network to be competitive with other traditional algorithms such as Genetic Algorithm (GA) and Simulated Annealing (SA) algorithm in solving PFLP problem and other constrained problems.