Solving One-Million-Bit Problems using LZWGA

To solve a problem using genetic algorithm (GA), a solution must be encoded into a binary string. The length of this string represents the size of the problem. As the length of the binary string increases, the size of the search space also increases at an exponential rate. To reduce the search space, one approach is to use a compressed encoding chromosome. This work proposes LZWGA that used compressed chromosomes. An LZWGA chromosome has to be decompressed using an LZW decompression algorithm before its fitness can be evaluated. The paper reports how to solve one-million-bit OneMax, royal road and trap functions using LZWGA. The search space of the original problem is 2^10000000 or about 9.90times10³⁰¹⁰²⁹ points. When using a compressed encoding, the search space was reduced to 8.37times10¹⁶⁶⁷¹⁷ points. The result from the experiment shows that it is practical to solve the problem of this size with the proposed method