An Approach to Consider Diversity Issues from a Semantic Point of View

In this paper, we discuss a semantic and application-driven approach to estimate diversity respectively similarity in Genetic Algorithms (GA) based on a relative distance. This diversity metric can used to decide, whether or not a new individual meets a requested degree of diversity. Furthermore, the trade-off between several versions of the metric and their computational complexity is discussed. Finally, the application of this metric and a formerly developed Backtrack- and Restart GA to solve the Travelling Salesman Problem under certain real time requirements is introduced along with experimental evaluation.

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