基于差分进化的卫星布局优化设计混合算法

Xianqi Chen, Wen Yao, Yong Zhao, Xiaoqian Chen, Jun Zhang, Yazhong Luo
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引用次数: 7

摘要

卫星布局优化设计(SLOD)问题是一类具有复杂性能约束的三维布局问题,被称为np困难问题。为了高效地解决SLOD问题,本文提出了两种基于差分进化(DE)的混合优化算法。针对卫星姿态控制分系统的设计要求,提出了SLOD问题,旨在提高卫星的整体质量特性。为了在全局范围内探索布局设计空间,将DE算法作为混合算法的主要框架。然后,为了提高局部开发能力和算法的鲁棒性,将序列二次规划(SQP)作为一种基于梯度的方法,以两种独特的方式与遗传算法相结合,构成两种混合算法。在第一类混合算法(DESQP)中,当DE的迭代过程结束时进行SQP,仅将DE的最终解作为SQP的起始点,其目的是首先利用DE找到最有希望的最优区域,然后围绕准最优进行快速开发。第二类混合算法(称为DESQPDE)在DE的特定迭代中进行SQP,并将所有当代种群个体作为初始点,目的是在保持种群多样性的同时加速进化过程,增强鲁棒性。最后,将混合算法的有效性和鲁棒性与经典DE进行了比较,并通过分别包含14个和40个组件的三维卫星布局案例进行了验证。
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The Hybrid Algorithms Based on Differential Evolution for Satellite Layout Optimization Design
The satellite layout optimization design (SLOD) problem is a kind of three-dimensional layout problems with complex performance constraints and known as a NP-hard problem. To solve SLOD problems efficiently and effectively, two types of hybrid optimization algorithm based on differential evolution (DE) are proposed in this paper. Concerning the design requirements of satellite attitude control subsystem, the SLOD problem is formulated, aiming to improve the overall mass characteristics of satellite. To explore the layout design space globally, the DE algorithm is utilized as the main framework of the proposed hybrid algorithm. Then in order to improve the local exploitation capability and algorithm robustness, sequential quadratic programming (SQP), as a gradient-based method, is combined with DE in two unique ways, comprising two types of hybrid algorithm. In the first type of hybrid algorithm (denoted by DESQP), SQP is performed when iteration process of DE has finished and only the final solution of DE is used as the initial point of SQP, the purpose of which is to locate the most promising area of optimum with DE first and then make a rapid exploitation around the quasi-optimum. In the second type of hybrid algorithm (denoted by DESQPDE), SQP is performed in the specific iteration of DE and all the current-generation population individuals are used as the initial points, the purpose of which is to accelerate the evolution process while holding the diversity of the population and to enhance the robustness. Finally, the efficacy and robustness of the proposed hybrid algorithms are compared with classical DE and also validated by two three-dimensional satellite layout cases with 14 and 40 components, respectively.
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