Kapsokalivas L, Gan X, Albrecht A A, Steinhöfel K
King's College London, Department of Computer Science, London WC2R 2LS, England, United Kingdom.
Comput Biol Chem. 2009 Aug;33(4):283-94. doi: 10.1016/j.compbiolchem.2009.06.006. Epub 2009 Jul 3.
We present experimental results on benchmark problems in 3D cubic lattice structures with the Miyazawa-Jernigan energy function for two local search procedures that utilise the pull-move set: (i) population-based local search (PLS) that traverses the energy landscape with greedy steps towards (potential) local minima followed by upward steps up to a certain level of the objective function; (ii) simulated annealing with a logarithmic cooling schedule (LSA). The parameter settings for PLS are derived from short LSA-runs executed in pre-processing and the procedure utilises tabu lists generated for each member of the population. In terms of the total number of energy function evaluations both methods perform equally well, however, PLS has the potential of being parallelised with an expected speed-up in the region of the population size. Furthermore, both methods require a significant smaller number of function evaluations when compared to Monte Carlo simulations with kink-jump moves.
我们展示了针对三维立方晶格结构中基准问题的实验结果，使用宫泽 - 杰尔尼根能量函数，针对两种利用拉移集的局部搜索程序：(i) 基于种群的局部搜索 (PLS)，它通过朝着（潜在的）局部最小值的贪婪步骤遍历能量景观，随后朝着目标函数的某个水平向上步长；(ii) 具有对数冷却时间表的模拟退火 (LSA)。PLS 的参数设置源自预处理中执行的短 LSA 运行，并且该程序利用为种群的每个成员生成的禁忌列表。就能量函数评估的总数而言，两种方法表现相当，但 PLS 具有并行化的潜力，预计在种群规模区域内加速。此外，与具有扭结跳跃移动的蒙特卡罗模拟相比，两种方法都需要显著更少的函数评估。
