考虑道路状况的应急配发站启用以及配送优化问题*

为了研究应急物资配发站启用及配送方案优化问题,综合考虑灾难事件下的道路损毁状况、道路复杂程度、需求不确定以及物资拆分配送等特点,以应急物资配发站启用成本、车辆启动成本、运输成本之和最小化为目标,建立应急物资配发站启用及配送模型,设计头脑风暴优化算法,结合算例,对该问题进行仿真,并将结果与遗传算法进行对比,验证模型的可行性和算法的有效性。结果表明,在决策时考虑道路状况能够有效降低系统成本,提高救援效率。     

Optimizing the Monitoring Strategy of Wastewater Treatment Plants by Multiobjective Neural Networks Approach

This paper applies artificial neural network (ANN) to model the observed effluent quality data. The ANN’s structure, involving the number of hidden layer and node and their connection, is determined endogenously by resorting to the compromise of data cost minimization and prediction accuracy maximization. To obtain the best compromise possible, the model introduces an aspiration variable (μ) that represents the level of aspiration achieved in one objective and the conjugate of μ, (1 − μ), represents level of aspiration achieved in the other objective. Because a massive amount of calculation is required, the model applies genetic algorithm (GA) for its computational flexibility and capability to ensure global solution. Feasibility and practicality of the model is tested by a case study with a set of 150 daily observations on 17 operational variables and quality parameters at an industrial wastewater treatment plant (WTP) located in southern Taiwan. Of these 17 variables open to selection, only 6 variables, wastewater flow rate (Q), CN⁻, SS, MLSS, pH and COD are selected by the model to achieve the maximum accuracy of prediction, 0.94, with a total cost of 5,950 NT$. By constraining budget availability, the variables included in the model are reduced in number, causing a concomitant reduction in prediction accuracy, that is, by varying μ (aspiration level of accuracy), a trajectory of cost and accuracy is generated. The calculation results a cost of 3,650 NT$ and 0.54 accuracy for the case with variables including flow rate, SCN⁻ and SS in equalization basin; aeration tank hydraulic retention time (HRT) and percentage of returned sludge (R%) are selected for building the prediction model when the importance of required budget is equal to the accuracy of prediction model. In addition, when required cost for building ANN model is between 3,650 NT$ and 3,900 NT$, the marginal return of budget input is highest in the entire range of calculation.     

射线追踪中与地形的加速技术研究

在采用射线追踪方法的仿真软件中，一般都会判断射线与地形的交点，从而判断射线与哪块地形发生相交和反射、绕射。目前地形多采用三角面的形式来模拟。而一条射线对较大地形所有三角面进行一次相交的判定的过程较长。就射线与地形判断相交和确定交点的位置的过程中估计射线路径从而减少与三角面的相交判断从而进行加速，从而使得射线追踪时间能够大幅度的缩短，提高了软件仿真的效率。     

雷电灾害风险评估系统开发与应用

根据国标《GB/T21714.2-2008雷电防护》的雷电灾害风险评估原理和方法,结合国标《GB50057-1994(2000年版)建筑防雷设计规范》和《GB50343-2004建筑物电子信息系统防雷技术规范》的相关方法,利用Del-phi7.0开发了集评估项目地理位置定位、闪电资料分析、建筑物评估和区域评估等功能的综合性雷电灾害风险评估系统。介绍了系统的需求分析、功能、特点和其中涉及的风险评估算法。利用该系统可快速、方便地完成各类项目雷电灾害风险评估工作,并自动生成word报告。     

Comparison of Aerosol Size-Distributions Using Linear-Regression, Genetic Algorithm, and Annealing Genetic Algorithm

Abstract Stability and accuracy of retrieving the aerosol size-distribution by using the linear-regression (LR), genetic algorithm (GA), and annealing genetic algorithm (AGA) were studied in detail. It was found that by using the AGA, retrieval results are quite stable and accurate; using the GA, stability and accuracy of the retrieval results decreased mildly but were still acceptable; and using the LR, retrieval results were too unstable to be acceptable. This conclusion is verified by both of the numeric simulation and the experiment.     

Optimization of test interval for ageing equipment: A multi-objective genetic algorithm approach

Reducing the unavailability of safety systems at nuclear power plants, by utilizing the probabilistic safety assessment (PSA) methodology, is one of the prime goals in the nuclear industry. In that sense, optimization of test and maintenance activities, which are defined within the technical specifications, represents quite popular and interesting domain. Obtaining optimal test and maintenance schedule is of great significance for improving system availability and performance as well as plant availability in general.On the other side, equipment aging has gradually become a major concern in the nuclear industry since the number of safety systems components, that are approaching their wear-out stage, is rising fast. Nuclear power plants life management programs, considering safety components aging, are being developed and employed. The immense uncertainty associated to the available component aging rates databases poses significant difficulties in the process of incorporation and quantification of the aging effect within the PSA and, subsequently, in the decision-making process.In this paper, an approach for optimization of surveillance test interval of standby equipment with highly uncertain aging parameters, based on genetic algorithm technique and PSA, is presented. A standard standby safety system in nuclear power plant is selected as a case study. A Monte Carlo simulation-based approach is used to assess uncertainty propagation on system level. Optimal test interval is derived on the basis of minimal system unavailability and minimal impact of components aging parameters uncertainty. The results obtained in this application indicate the fact that risk-informed surveillance requirements differ from existing ones in technical specifications as well as show the importance of considering aging data uncertainties in component aging modeling.     

Dependability assessment of network-based safety-related system

Advances in electronic integration and radio communication have led to the emergence of a new kind of safety systems, i.e. Wireless Sensor Network (WSN). This network-based safety-related system is becoming more and more present in the domain of safety due to its easy deployment. It does not need a wire infrastructure and its range of applications is wide. Usually, such a system is composed of various nodes (sensors) collaborating to monitor a targeted phenomenon. In most cases, nodes are battery powered and this is the weakness of the system makes it necessary to design an energy saving policy. The present paper gives a dependability viewpoint of such a system. A modeling framework is suggested integrating the interdependency of the components. Stochastic Petri nets are used to implement this model and two heuristics to schedule component activity. The first is based on the proposed importance measures, the second on a multi-objective genetic algorithm. The aim is to conserve energy and so to extend WSN dependability.     

基于运行安全的停机位分配问题研究

随着民航运输业的发展,航班密度不断增加,相邻停机位间推出冲突概率不断增加。为合理分配大型繁忙机场停机位,兼顾安全与效率,建立基于运行安全的停机位分配问题优化模型。在模型中加入约束条件以避免潜在的推出冲突,以及考虑将重要航班优先分配到指定的旅客行走距离较短的停机位,来提高旅客的整体满意度。通过分析机位分配特点,选择性能比较优越的遗传算法进行求解。最后用实际算例进行验证,得到停机位分配甘特图以及算法收敛曲线。从结果中可以看到,停机位分配比较合理,算法收敛性能良好。就整体而言,达到了预期的要求。     

人员非均匀分布条件下的疏散引导方向优化算法研究

在紧急疏散中,疏散引导标识或疏散引导人能够帮助人员快速找到最近出口,有效减少疏散时间。疏散引导标识或人的引导方向一般是根据建筑布局情况预先进行设计,当前位置的引导方向指向最近的疏散出口。本文综合考虑了建筑布局及人员分布情况,提出了人员非均匀分布条件下的疏散引导方向优化算法。该算法以Togawa疏散时间经验公式作为估价函数,通过多次迭代的方法,求解疏散引导方向的优化值。以双出口的疏散场景为例,利用疏散软件Legion对优化前后疏散引导方向下的疏散时间进行了比较分析。结果表明,优化后的疏散引导方向能够引导人员充分利用疏散出口,疏散时间较仅考虑建筑布局所设计的疏散引导方向的模拟值降低了近四分之一,大大提高了疏散效率。