A Memetic Algorithm for Reconstructing Cross-Cut Shredded Text Documents

The reconstruction of destroyed paper documents became of more interest during the last years. On the one hand it (often) occurs that documents are destroyed by mistake while on the other hand this type of application is relevant in the fields of forensics and archeology, e.g., for evidence or restoring ancient documents. Within this paper, we present a new approach for restoring cross-cut shredded text documents, i.e., documents which were mechanically cut into rectangular shreds of (almost) identical shape. For this purpose we present a genetic algorithm that is extended to a memetic algorithm by embedding a (restricted) variable neighborhood search (VNS). Additionally, the memetic algorithm's final solution is further improved by an enhanced version of the VNS. Computational experiments suggest that the newly developed algorithms are not only competitive with the so far best known algorithms for the reconstruction of cross-cut shredded documents but clearly outperform them.