The aim of this project was to investigate a combinatorial optimization problem stated by Global Genomics AB. The problem has its background in genomics, and is part of a new method for measuring gene expression levels. This method involves experiments as well as post processing of the experimental data. The experiments take a cell sample as input, and the output is incomplete information about the genes expressed in the sample. To estimate the gene expression levels from this information, it has to be matched with a gene database. Since the experimental data is incomplete, there are many possible matchings. The problem investigated in this project is to find the best matching between the experimental data and the gene database, using some different local search techniques.