Abstract
Evolutionary algorithms (EAs) have been used in varying ways for design and other creative tasks. One of the main elements of these algorithms is the fitness function used by the algorithm to evaluate the quality of the potential solutions it proposes. The fitness function ultimately represents domain knowledge that serves to bias, constrain, and guide the algorithm’s search for an acceptable solution. In this paper, we explore the degree to which the fitness function’s implementation affects the search process in an evolutionary algorithm. To perform this, the reliability and speed of the algorithm, as well as the quality of the designs produced by it, are measured for different fitness function implementations. These measurements are then compared and contrasted.
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Acknowledgments
This work has been supported by Asociación Mexicana de Cultura, A.C.
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© 2016 Springer International Publishing Switzerland
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de Silva Garza, A.G. (2016). Comparing Different Implementations of the Same Fitness Criteria in an Evolutionary Algorithm for the Design of Shapes. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_20
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DOI: https://doi.org/10.1007/978-3-319-19090-7_20
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