论文部分内容阅读
针对三维卫星舱布局优化问题(three-dimensional satellite module layout optimization problem,3DSMLOP),本文提出了一种具有双邻域的改进人工蜂群算法,并将其与多阶段求解策略结合,形成多阶段双邻域人工蜂群算法(multi-stage dual neighborhood artificial bee colony algorithm,MS-DABC).3DSMLOP是一个复杂的多约束耦合问题,其解空间是非连续、非线性、多模态的.MS-DABC将3DSMLOP分解为多个子系统,并根据优化目标在各个子系统之间的耦合关系,将优化过程分为两个阶段.第一阶段,针对无耦合的优化目标,各个子系统利用具有双邻域结构的改进人工蜂群算法独立进行优化.在第一阶段求得的最优解的基础上,第二阶段采用一般人工蜂群算法来优化子系统的旋转角度,利用各个子系统之间的协同旋转来解决耦合的优化目标.仿真实验结果表明,该算法求解复杂的卫星舱布局问题非常有效,在3DSMLOP算例求解上性能突出.
In order to solve the problem of three-dimensional satellite module layout optimization (3DSMLOP), an improved artificial bee colony algorithm with dual neighborhoods is proposed and combined with the multi-stage solution strategy to form a multi-stage double MS-DABC) .3DSMLOP is a complex multi-constraint coupling problem whose solution space is discontinuous, nonlinear and multi-modal.MS-DABC The 3DSMLOP is decomposed into several subsystems and the optimization process is divided into two phases according to the coupling relationship between the optimized subsystems in each subsystem.In the first phase, for the non-coupling optimization target, each subsystem utilizes a two-neighborhood structure The improved artificial bee colony algorithm is optimized independently.On the basis of the optimal solution obtained in the first phase, the general artificial bee colony algorithm is used in the second phase to optimize the rotation angle of the subsystem, and the synergetic rotation between the subsystems To solve the coupled optimization goal.The simulation results show that the algorithm is very effective in solving the complex satellite cabin layout problem and is solved in the 3DSMLOP case Outstanding performance.