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

• Published in: Computer Aided Systems Theory - EUROCAST 2013 pp. 380 - 387
• Main Authors: Biesinger, Benjamin, Schauer, Christian, Hu, Bin, Raidl, Günther R.
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg
• Series: Lecture Notes in Computer Science
• Subjects: genetic algorithm; reconstruction; solution archive
• ISBN: 364253855X; 9783642538551
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-53856-8_48

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.