基于流场数值模拟的导流堤加固方案优化设计

流态和流速分析是导流堤设计的先决问题。以某沿海水利枢纽导流堤为研究对象,采用有限元数值模拟的手段及平面二维水流数学模型,对其加长加固方案进行对比分析,优选出合理的导流堤结构型式和长度,为工程设计提供理论参考。     

湿法炼锌沉铁过程氧化速率优化控制

湿法炼锌沉铁过程针铁矿沉淀形成的条件要求苛刻, 亚铁离子的氧化速率必须控制在合理的范围内才能保证溶液中的铁离子以针铁矿形式除去. 本文在沉铁过程动态模型的基础上, 根据针铁矿沉淀形成的条件和结合流程工艺要求, 优化设定每个反应器出口的亚铁离子浓度, 进而建立针铁矿法沉铁过程氧化速率优化控制模型. 采用控制参数化方法将最优控制求解问题转化为非线性规划, 通过状态转移优化算法求取最优的氧气和氧化锌控制率, 以合理控制沉铁过程亚铁离子的氧化速率. 仿真结果表明, 优化控制模型计算所得的控制量不仅可以保证反应过程的氧化速率符合生成针铁矿沉淀的条件, 而且可以稳定生产流程.     

基于混合遗传算法的去耦电容网络设计

结合基于目标阻抗的设计方法,将混合遗传算法应用于PDN(电源分配网络)的去耦电容网络设计,对所需去耦电容器的种类和数目进行优化计算,同时与标准遗传算法和传统设计方法进行对比,借助Cadence电源完整性仿真工具验证设计结果的有效性和合理性。避免了传统设计需要借助EDA工具进行反复修改和验证的繁琐过程,同时减少了设计冗余,节省了PCB布局布线空间,为高频电路的PDN设计提供参考。     

融合张角拥挤控制策略的高维多目标优化

对于高维多目标优化问题,随着目标维数的增加,种群中非被支配解的比例剧增, 严重降低了种群的进化压力.为了对数量众多的非被支配解进行有效的拥挤控制并提升种群的多样性, 本文在提出张角概念的基础上设计了一种新的拥挤控制策略(Congestion control strategy based on open angle, CCSOA),它的时间复杂度并不会随着目标维数的增加而增大. 与目前优秀的进化多目标优化(Evolutionary multiobjective optimization, EMO)算法IBEA (Indicator-based evolutionary algorithm)、NSGAIII (Nondominated sorting genetic algorithm III)和GrEA (Grid-based evolutionary algorithm)的比较结果表明, 融合了CCSOA的高维多目标优化算法在收敛效果和解集分布的均匀性两个方面均有较大的优势.     

具备反向学习和局部学习能力的粒子群算法

为解决粒子群优化（Particle Swarm Optimization,PSO）算法中存在的种群多样性和收敛性之间的矛盾,该文提出了一种具备反向学习和局部学习能力的粒子群优化算法（Reverse-learning and Local-learning PSO,RLPSO）。该算法保留了初始种群中满足排异距离要求的多个较差粒子以及每个粒子的历史最差位置。当检测到算法陷入局部最优时,利用这些较差粒子的位置信息指导部分粒子以较快飞行速度进行反向学习,将其迅速牵引出局部最优区域。反向学习过程可改善粒子种群的多样性,保证了算法的全局探测能力;同时,利用较优粒子间的差分结果指导最优粒子进行局部学习与搜索,该过程可与粒子群的飞行过程并行执行,且局部学习的缩放因子可随进化过程动态调节。局部学习可提高算法的求解精度,保证算法的迅速收敛。实验结果表明,RLPSO 算法同其他 PSO 算法相比,在高维函数优化中具有收敛速度快、求解精度高的特点。     

Infra-chromatic bound for exact maximum clique search

Many efficient exact branch and bound maximum clique solvers use approximate coloring to compute an upper bound on the clique number for every subproblem. This technique reasonably promises tight bounds on average, but never tighter than the chromatic number of the graph.Li and Quan, 2010, AAAI Conference, p. 128–133 describe a way to compute even tighter bounds by reducing each colored subproblem to maximum satisfiability problem (MaxSAT). Moreover they show empirically that the new bounds obtained may be lower than the chromatic number.Based on this idea this paper shows an efficient way to compute related “infra-chromatic” upper bounds without an explicit MaxSAT encoding. The reported results show some of the best times for a stand-alone computer over a number of instances from standard benchmarks.     

An anticipation mechanism for the shortest path problem based on Physarum polycephalum

In this paper, we put forward an anticipation mechanism for the existing Physarum-inspired shortest path finding method. The Physarum-based shortest path finding model can be implemented by an iterative algorithm and has wide applications in many fundamental network optimization problems. In this paper, we mainly focus on the Physarum-inspired shortest path tree model. Normally, we stop the program when the difference between two consecutive iterations is less than a predefined threshold. However, we do not know how to set the specific value for the threshold variable. In order to find out the optimal solution, we need to set the threshold as a very small number. This in turn will consume a lot of time. From this point of view, this algorithm lacks an efficient and reliable mechanism to judge when the optimal solution will be found. In this paper, we introduce an anticipation mechanism to address this issue. Numerical examples are used to demonstrate its reliability and efficiency.