Evolution trategy and ierarchical lustering
O. Aichholzer, F. Aurenhammer, B. Brandtstaetter, H. Krasser,
C. Magele, M. Muehlmann, and W. Renhart
Multi-objective optimization problems, in general, exhibit several local optima
besides a global one. A desirable feature of any optimization strategy would
therefore be to supply the user with as many information as possible about
local optima on the way to the global solution. In this paper a hierarchical
clustering algorithm implemented into a higher order Evolution Strategy is
applied to achieve these goals.
Reference: O. Aichholzer, F. Aurenhammer, B. Brandtstaetter, H. Krasser,
C. Magele, M. Muehlmann, and W. Renhart.
Evolution trategy and ierarchical lustering.
In COMPUMAG Conference on the Computation of Electromagnetic
Fields, Lyon-Evian, France, 2001.