Parallelization of Evolution Strategy on a Workstation-Cluster and its Application to Discrete Structural Optimization
Keyword(s):
Abstract Evolution strategies (ESs) imitate biological evolution and have two characteristics that differ from other conventional optimization algorithms: (a) ESs use randomized operators instead of the usual deterministic ones; (b) instead of a single design point, the ESs work simultaneously with a population of design points in the space of variables. The second characteristic allows for an implementation in a parallel computing environment. In this paper the application of ESs for the solution of discrete optimization problems and its parallelization are described.
2015 ◽
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2010 ◽
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