微波接力组网的节点再优化研究

为进一步完善常规方法构建的微波接力网组网拓扑,提出了一种基于最优链路集的网络节点再优化方法。该方法综合考虑节点吸引系数、链路衰落概率、节点通信冗余等因素,借助网络拓扑优化的思想,采用遗传算法构造了微波接力网的最优链路集;以节点在该集合中的度为依据,通过对节点的合理排序,以部分用户节点代替非必要的干线节点,完善了组网拓扑。在修改链路和节点价值集后,该方法还可解决其他网络干线、中继节点的选择问题。     

基于改进智能水滴算法的动态车辆配送路径优化

针对当前车辆配送过程中存在的配送路径不合理、配送效率低和需求不确定性等问题,提出一种基于改进智能水滴算法的动态车辆配送路径优化方法。构建软时间窗惩罚函数,考虑顾客对配送时间的要求,建立顾客满意度函数。综合车辆配送过程的车速、货损成本、惩罚成本、顾客满意度等特征,建立车辆路径优化模型。采用智能水滴算法对车辆路径优化模型进行求解,使用灰狼优化算法改善智能水滴算法的搜索能力,获取最优路径。实验结果表明该方法能够提供实时优化的路径,减少调配成本。     

实现船舶稳性的多油舱自适应调度算法及仿真

针对油舱对船舶浮态与稳性的影响，研究了保持船舶稳性的多油舱自适应调度控制算法，并用WinCC (Windows Control Center)组态软件编写了船舶自动浮态调整仿真系统。在系统架构上，采用布尔逻辑表构建了油舱、泵、管路之间的连通关系，并根据浮态方程计算出舱群之间的调驳油量，再根据多变量多约束的自适应优化调度算法实现了油舱驳油过程中浮态的平衡。仿真结果表明调度算法可以对船舶的浮态进行有效调整，并保持船舶稳性，避免了由油舱油量分布不均给船舶带来的不利影响，保障了航行安全。     

基于模型的多目标优化问题方法研究

基于模型的多目标优化方法目的是创新一种通过黑箱评估的多目标函数优化算法,该算法从解空间上的混合分布中迭代生成候选解,并根据采样解的控制数来更新混合分布,求解过程的搜索偏向于Pareto最优解的集合。算法在解空间上寻找混合分布,使得混合分布的每个分量都是以帕累托最优解为中心的简并分布,并且每个预计的Pareto最优解都通过一个阈值距离均匀地分布在Pareto最优解集上,实验通过几个基准函数和方法证明了该算法的性能。     

基于共识粒子群的全局优化求解方法

针对粒子群优化(PSO, particle swarm optimization)和高效全局优化(EGO, efficient global optimization)两种算法的特点,提出一种共识粒子群和局部代理模型协同的全局黑箱优化算法(CPSO-LSM, consensus particle swarm optimization and local surrogate model)。该算法固定PSO算法周期对粒子进行分群并在粒子达成共识后停止,将每群粒子周围的优质子区域输出作为代理模型的建模区域,通过比较各区域最优值获得高质量最优解甚至全局最优解。不仅避免了PSO冗长的计算过程、提高了建立代理模型的速度和精度还可以避免陷入局部最优。通过对比其他算法在标准测试函数的仿真结果,CPSO-LSM具有较好的收敛速度和求解精度。     

考虑动态多时段借还车需求的城市自行车租赁系统规划模型

建立了一个自行车租赁系统规划模型。该模型考虑一天中动态的自行车借还车需求及租赁分区自行车和空闲停车位数量的动态变化，通过优化各租赁分区的自行车停车桩(或对共享单车为停车位)数量，以及运营时段初始各小区分配的自行车数量，在保证所有的自行车借还车需求均能得到满足的基础上，最小化总的投资建设成本。模型为一个大型整数线性规划问题，通过LINGO软件中内置的分支定界算法，可快速求得全局最优解。通过算例对该模型进行了验证。     

The ecological rationality of explanatory reasoning

There is growing evidence that explanatory considerations influence how people change their degrees of belief in light of new information. Recent studies indicate that this influence is systematic and may result from people’s following a probabilistic update rule. While formally very similar to Bayes’ rule, the rule or rules people appear to follow are different from, and inconsistent with, that better-known update rule. This raises the question of the normative status of those updating procedures. Is the role explanation plays in people’s updating their degrees of belief a bias? Or are people right to update on the basis of explanatory considerations, in that this offers benefits that could not be had otherwise? Various philosophers have argued that any reasoning at deviance with Bayesian principles is to be rejected, and so explanatory reasoning, insofar as it deviates from Bayes’ rule, can only be fallacious. We challenge this claim by showing how the kind of explanation-based update rules to which people seem to adhere make it easier to strike the best balance between being fast learners and being accurate learners. Borrowing from the literature on ecological rationality, we argue that what counts as the best balance is intrinsically context-sensitive, and that a main advantage of explanatory update rules is that, unlike Bayes’ rule, they have an adjustable parameter which can be fine-tuned per context. The main methodology to be used is agent-based optimization, which also allows us to take an evolutionary perspective on explanatory reasoning.     

Shift-contagion in energy markets and global crisis

This paper presents an analysis of shift-contagion in energy markets, testing whether linkages between returns in energy markets increase during crisis periods. The research presented herein demonstrates how common movement between energy markets increases due to (i) shift-contagion across energy markets, reflected by structural transmission of shocks across markets and (ii) larger common shocks operating through standard cross-market interdependences. A regime-switching model was developed to detect shift-contagion across energy markets. In the approach adopted herein, the occurrence of shift-contagion is endogenously estimated rather than being exogenously assigned. The results show that shift-contagion has been a major feature of energy markets over the last decade. Evidence is presented which demonstrates that the linkages between energy markets do not appear to be stable. These results are remarkably accurate for forecasting Brent and natural gas for horizons for up to 50 days. Conversely, for WTI (West Texas Intermediate oil) and coal, the model performs well only for forecasting very short horizons (up to 20 days). For all products, the model shows significant biases for long horizons.     

盐胁迫对大花四照花种子萌发与幼苗生长的影响

探究盐胁迫对大花四照花种子萌发及幼苗生长的影响，为大花四照花在滨海地区的推广提供理论依据。     

媒体监督与控股股东侵占——一个理论框架

本文利用随机动态优化工具建立理论模型,对媒体监督与控股股东侵占行为进行了研究.结论表明,控股股东侵占损害中小股东福利,增大公司风险;媒体监督对控股股东自身福利产生双重效应——财富分配效应和资产减值效应,控股股东最优侵占比例取决于这两种效应的相对强弱;提高媒体对控股股东侵占现象反应的敏感性,增强曝光力度,能够迫使控股股东更加重视自身声誉,减少对中小股东利益的侵占;控股股东与媒体的合谋会使其更加大胆地通过侵占中小股东利益,提高自身福利.