A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
A Review of Constraint-Handling Techniques for Evolution Strategies
2010
Applied Computational Intelligence and Soft Computing
Evolution strategies are successful global optimization methods. In many practical numerical problems constraints are not explicitly given. Evolution strategies have to incorporate techniques to optimize in restricted solution spaces. Famous constraint-handling techniques are penalty and multiobjective approaches. Past work has shown that in particular an ill-conditioned alignment between the coordinate system of Gaussian mutation and the constraint boundaries leads to premature convergence.
doi:10.1155/2010/185063
fatcat:x6s5c75tcveodoeoaq6nhyynqq