An Evaluation of the Convergence Properties of a Parallel Genetic Programming Method

Abstract

Genetic programming is a technique that produces as output the source code of another computer program. The program is evolved with rules of natural selection that seek to find the best solution to a particular problem. This report presents the results of tests run on eight different GP method parameters and shows how variations in the value of these parameters affects the time taken to converge on the correct solution. The problem used to test the method is the MAX problem which proved to be a simple, straight forward, and easy approach for evaluating GP efficiency. Testing the method on the MAX problem can help to develop an optimum search for problems with unknown solutions. This paper presents the results of this study.