Balance Algorithm for Point-Feature Label Placement Problem

  • Zheng He
  • Koichi Harada
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3696)


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.


Genetic Algorithm Simulated Annealing Penalty Function Valid Solution Balance Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Zheng He
    • 1
  • Koichi Harada
    • 2
  1. 1.Graduate School of EngineeringHiroshima UniversityJapan
  2. 2.Department of Integrated Arts & SciencesHiroshima UniversityJapan

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