A Novel Design Approach of High Temperature Superconducting Magnets by Cultural Evolution Algorithms

The superconducting magnets have many advantages compared with conventional electromagnets. A novel design approach is presented in this paper for the high temperature superconducting magnets by the cultural evolution algorithm. First of all, the optimization model of high temperature superconducting magnet is constructed. Secondly, the feasible solutions of the optimization model are encoded as individuals; the better individuals are produced by the cultural evolution algorithm. The cultural evolution algorithm consists of three major components: a population space, a belief space, and a communication protocol. The chaotic maps and particle swarm optimization are used in the evolutionary procedure of the individuals in the population space and belief space. The experimental results show that the superconducting magnets with the better volume of solenoid coils can be obtained by the approach proposed in this paper.