A comparison of bloat control methods for genetic programming
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Unnecessary growth in program size is known as bloat problem in Genetic Programming. There are a large number of studies addressing this problem. In this paper, we propose an effective bloat control mechanism which is based on examining the contribution of each function node in the selected programs. Nodes without contribution will be removed before generating offspring. The results show that the method can significantly reduce program size without compromising fitness. Furthermore it speeds up evolution processes because of the saving in evaluation costs.