Many institutions have powerful computers sitting idle much of the time. It would be a great use of this spare computation power to be harnessed to help solve problems that currently take substantial time to calculate on computationally busy machines. This thesis explores the possibilities of using simple socket based tools to utilize the available surplus computing power for the potentially parallelizable calculation of complex algoritkms, as well as changes needed in a simple Genetic Algorithm to be solved using this tool. This thesis discusses the development of a distributed genetic algorithm solution tool, broken into two parts; the genetic algorithm itself, and the general-purpose distribution tool for generating and tracking all the partial solutions during the main computation, as well as managing a fair use of all interested machines.