Higher order evolution strategies for the global optimization of electromagnetic devices

Basic evolution strategies (ESs) utilizing simplified features of biological evolution like mutation and selection are applied to solve problems of parameter identification for the optimal design of electromagnetic devices. Their main advantage lies in their stable convergence behavior and their self-adapting stepwidth sigma . Higher order ( mu / rho , lambda ) evolution strategies can be successfully applied to multimodel problems. To ensure at least a result very near the global optimum, a theory of disaster can be introduced. After a certain number of standard generations, the stepwidth sigma is increased greatly for a specified number of generations. Descendants arrived at during these generations are more likely to escape a local minimum than ordinary descendants. ( mu / rho , lambda ) evolution strategies can be easily implemented on parallel computers, helping to reduce the real-time requirements for one generation.<
>