Distance-Targeting Mutation Operator for Evolutionary Design of 3D Structures

Evolutionary design of 3D structures - an automated design by the methods of evolutionary algorithms - is a hard optimization problem. One of the contributing factors is a complex genotype-to-phenotype mapping often associated with the genetic representations of the designs. In such case, the genetic operators may exhibit low locality, i.e., a small change introduced in a genotype may result in a significant change in the phenotype and its fitness, hampering the search process. To overcome this challenge in evolutionary design, we introduce the Distance-Targeting Mutation Operator (DTM). The aim of this operator is to create offspring whose distance to the parent solution, according to a selected dissimilarity measure, approximates a predefined value. We compare the performance of the DTM operator to the performance of the mutation operator without parent-offspring distance control in a series of evolutionary experiments. We use different genetic representations, dissimilarity measures, and optimization goals, including velocity and height of active and passive 3D structures. The introduced DTM operator outperforms the standard one in terms of best fitness in most of the considered cases.