The NURBS book
The String-to-String Correction Problem
Journal of the ACM (JACM)
Evolution and Optimum Seeking: The Sixth Generation
Evolution and Optimum Seeking: The Sixth Generation
Optimisation of Density Estimation Models with Evolutionary Algorithms
PPSN V Proceedings of the 5th International Conference on Parallel Problem Solving from Nature
Selected Papers from AISB Workshop on Evolutionary Computing
Morphing Using Curves and Shape Interpolation Techniques
PG '00 Proceedings of the 8th Pacific Conference on Computer Graphics and Applications
Curve Morphing by Weighted Mean of Strings
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 4 - Volume 4
A memetic algorithm for efficient solution of 2D and 3D shape matching problems
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
| Hi-index | 0.00 |
Design optimization is a well established application field of evolutionary computation. However, standard recombination operators acting on the genotypic representation of the design or shape are often too disruptive to be useful during optimization. In this work, we will analyze whether morphing methods between two shapes can be used as recombination operators acting on the phenotype space, thus directly on the shape or design. We introduce three different morphing methods and employ them as recombination operators in a standard evolution strategy (es). We compare their performance with an evolution strategy without any recombination operators on two target shape approximation problem. We can conclude that two of the three morphing methods can be useful during search although all morphing methods still turn out to hinder the self-adaptation of the step sizes of the evolution strategy.