Distributed niching concept for electromagnetic shape optimization by genetic algorithm

Generic algorithms are becoming a common tool for optimal design applications, where, due to multiple solutions, global search techniques are required. When dealing with real problems, involving several degrees of freedom, the computing power restricts the global search ability. New genetic techniques have been proposed for parallel architectures, allowing one to deal with real problems. One of these techniques, called the niching approach, can be implemented by dividing the population into subgroups, and letting each group to evolve on one of the processors, interacting only when scheduled. The authors discuss the niching approach in the optimal design of electromagnetic applications. As an example, some preliminary results on SMES (superconducting magnetic energy storage) devices are proposed