The main interest of this paper is to study the relationship between the low-discrepancy sequence and the static solution to the multi-bodies problem in high-dimensional space. An assumption that the static solution to the multi-bodies problem is a low-discrepancy sequence is proposed. Considering the static solution to the multi-bodies problem corresponds to the minimum potential energy principle, we further assume that the distribution of the bodies is the most uniform when the potential energy is the smallest. To verify the proposed assumptions, a dynamical evolutionary model (DEM) based on the minimum potential energy is established to find out the static solution. The central difference algorithm is adopted to solve the DEM and an evolutionary iterative scheme is developed. The selection of the mass and the damping coefficient to ensure the convergence of the evolutionary iteration is discussed in detail. Based on the DEM, the relationship between the potential energy and the discrepancy during the evolutionary iteration process is studied. It is found that there is a significant positive correlation between them, which confirms the proposed assumptions. We also combine the DEM with the restarting technique to generate a series of low-discrepancy sequences. These sequences are unbiased and perform better than other low-discrepancy sequences in terms of the discrepancy, the potential energy, integrating eight test functions and computing the statistical moments for two practical stochastic problems. Numerical examples also show that the DEM can not only generate uniformly distributed sequences in cubes, but also in non-cubes.
翻译:本文的主要兴趣是研究低差异序列与高空间多机体问题静态解决方案之间的关系; 假设多机体问题静态解决方案是一个低差异序列; 考虑到多机体问题静态解决方案与最小潜在能源原则相对应,我们进一步假设,当潜在能源最小时,机体分布是最统一的; 为了核实拟议的假设,根据最小潜在能源建立动态进化模型(DEM),以找出静态解决方案; 采用中央差异算法解决DEM, 开发进化迭接机制; 选择质量和阻隔系数以确保进化迭代机制趋同; 根据德国马克,研究潜在能源与进化变异过程中的差异之间的关系; 发现它们之间有显著的正相关关系,只能证实拟议的假设; 我们还将DEM与重新启动技术相结合,以产生一系列不易差异的静态解决方案, 并开发进化迭代办法; 选择质量和阻断系数系数,以确保进化迭代法的趋同; 根据德国马克, 潜在能量和进化过程中的进化变和进化过程,这些序列将产生更准确性和进化的序列; 数字序列,在统计序列中,这些序列中产生更精确和演化的变变变变。 这些序列中,在数字序列中,在数字序列中,这些序列中产生更佳的顺序和变变。