Multivariable Optimal Design of Vacuum Interrupter using Novel Self-adaptive Genetic Algorithm

Abstract

An improved self-adaptive genetic algorithm (GA) is introduced for efficiently optimizing the complex structure and multi-variants cases. In optimizing, alleles operation and self-adaptive adjustment of the crossover and the mutant operator have been realized. The feasibility and the validity of the proposed improved GA have been verified using the typical testing function. Furthermore, the optimization of a vacuum interrupter (VI) has been successfully accomplished using the proposed GA. In optimizing, the shape of the contact has been considered as the optimized variable, and the objective function is to minimize the maximum electric field strength. Moreover the simulation results have been figured out