| 陈羽,滕弘飞.变粒度协同进化设计算法及其在卫星舱布局设计中应用[J].,2010,(6):931-936 |
| 变粒度协同进化设计算法及其在卫星舱布局设计中应用 |
| Coevolutionary algorithm with coarse-to-fine grain strategy and its application to layout design of satellite module |
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| DOI：10.7511/dllgxb201006017 |
| 中文关键词: 协同进化 变粒度 布局设计 |
| 英文关键词: coevolution coarse-to-fine grain layout design |
| 基金项目:国家自然科学基金资助项目(5057503160674078)；“八六三”国家高技术研究发展计划资助项目(2006AA04Z109). |
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| 中文摘要: |
| 采用进化算法求解复杂卫星舱布局问题时，算法容易陷入局部最优，且干涉计算复杂度高，计算耗时长．为提高对复杂解空间的搜索能力，基于协同进化算法，将问题分解为若干子问题求解；为减少计算耗时，子问题求解时采用了一种设计变量的变粒度策略．称上述方法为变粒度合作式协同进化算法(CCEA-CFG)．卫星舱布局优化数值实验表明，与目前常用的几种布局求解算法(遗传算法、协同进化算法以及遗传/粒子群算法(QPGP))相比，CCGA-CFG(基于GA的CCEA-CFG)具有较好的计算质量、计算效率和计算鲁棒性． |
| 英文摘要: |
| The main problems for evolutionary algorithm to deal with the complex layout design of satellite module include easily being trapped into local optimality, high complexity of interference computation and large amount of consuming time. To enhance the global search ability in the complex solution space, the layout design problem was decomposed and cooperative coevolutionary algorithm was employed for optimization search. Meanwhile, in order to reduce the computational time, a coarse-to-fine grain strategy of design variables is presented and applied to the co-evolutionary search of the sub-problems. The proposed algorithm was called cooperative coevolutionary algorithm with coarse-to-fine grain strategy (CCEA-CFG). The experimental results in a layout design of satellite module show that, the CCGA-CFG (CCEA-CFG based on GA) not only enhances the quality of solution, but also shortens the consuming time and is more robust, in comparison with genetic algorithm (GA) cooperative coevolutionary GA and QPGP. |
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