Enhancing a Genetic Algorithm with a Solution Archive to Reconstruct Cross Cut Shredded Text Documents

  • Benjamin Biesinger
  • Christian Schauer
  • Bin Hu
  • Günther R. Raidl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8111)


In this work the concept of a trie-based complete solution archive in combination with a genetic algorithm is applied to the Reconstruction of Cross-Cut Shredded Text Documents (RCCSTD) problem. This archive is able to detect and subsequently convert duplicates into new yet unvisited solutions. Cross-cut shredded documents are documents that are cut into rectangular pieces of equal size and shape. The reconstruction of documents can be of high interest in forensic science. Two types of tries are compared as underlying data structure, an indexed trie and a linked trie. Experiments indicate that the latter needs considerably less memory without affecting the run-time. While the archive-enhanced genetic algorithm yields better results for runs with a fixed number of iterations, advantages diminish due to the additional overhead when considering run-time.


genetic algorithm solution archive reconstruction 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Benjamin Biesinger
    • 1
  • Christian Schauer
    • 1
  • Bin Hu
    • 1
  • Günther R. Raidl
    • 1
  1. 1.Institute of Computer Graphics and AlgorithmsVienna University of TechnologyViennaAustria

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