2维静磁场多参量微动粒子群优化算法

Jiggle particle swarm optimization algorithm for 2D magnetostatic multi-parameter problem

提出一种微动粒子群优化算法,针对2维静磁场多参量优化问题,在给出轴上目标轴向磁感应强度分布曲线的前提下,可以得到趋近于该分布曲线的磁结构。该算法分为前后两阶段:第一阶段采用前后试探法(微动),同时也参照最优粒子的信息;第二阶段采用基本粒子群优化算法。微动粒子群优化算法可以发挥多核计算机在工程设计上的潜力,而且即使粒子数目很少,也能不断趋近目标解。

Abstract：A jiggle particle swarm optimization（JPSO） algorithm has been presented for the multi-parameter optimization of 2D magnetostatic problem. Given a target curve of axial magnetic flux density along the axis of symmetry, it can find rotating axisymmetric magnetic structures whose distribution curve of magnetic flux dnesity is close to the target one. This algorithm is divided into two phases. In the first phase, up-and-down test method （jiggle） is adopted with continuous reference to the best particle’s information. In the second phase, basic particle swarm optimization algorithm is adopted. The JPSO algorithm shows multi-core computer’s potential in engineering design multi-parameter optimization of 2D magnetostatic problems. Even if there is only a few particles, its successive results can also approach target curve.