meta-heuristics for reconstructing cross cut shredded text documents
In this work, we present two new approaches based on variable neighborhood search (VNS) and ant colony optimization (ACO) for the reconstruction of cross cut shredded text documents. For quickly obtaining initial solutions, we consider four different construction heuristics. While one of them is based on the well known algorithm of Prim, another one tries to match shreds according to the similarity of their borders. Two further construction heuristics rely on the fact that in most cases the left and right edges of paper documents are blank, i.e. no text is written on them. Randomized variants of these construction heuristics are applied within the ACO. Experimental tests reveal that regarding the solution quality the proposed ACO variants perform better than the VNS approaches in most cases, while the running times needed are shorter for VNS. The high potential of these approaches for reconstructing cross cut shredded text documents is underlined by the obtained results.
variable neighborhood search ant colony optimization document reconstruction integer linear programming