Better Huffman Coding via Genetic Algorithm

We present an approach to compress arbitrary files using a Huffman-like prefix-free code generated through the use of a genetic algorithm, thus requiring no prior knowledge of substring frequencies in the original file. This approach also enables multiple-character substrings to be encoded. We demonstrate, through testing on various different formats of real-world data, that in some domains, there is some significant advantage to using this genetic approach over the traditional Huffman algorithm and other existing compression methods.