基于分级多目标决策的干线公交速度引导模型

为解决干线公交速度引导存在多要素关联约束强，全局效果差的问题，本文提出基于分级多目标决策的干线公交速度引导模型。基于公交线路运行特性的全局优化指标优势分析，设计以公交线路综合准点率为主，交叉口停车次数和分段引导速度均衡为辅的线路全局优化目标体系，并考虑多目标间的关联约束和优先控制差异，构建基于拉格朗日乘子法和遗传算法分层组合的干线公交速度引导分级多目标递阶决策模型；最后，通过实际场景测试，验证模型的有效性。测试结果表明：模型能够克服非全局指标优化的局部最优问题，将全线路各班次综合准点率和交叉口停车次数由非全局指标的69.67%和2.37次 ⋅ 班-1 提升到90.53%和1.23次 ⋅ 班-1；并且综合准点率比全局多目标加权方法提升8.65%，能够较好保障综合准点率目标的优先性，有效提升干线公交的通行效率和服务可靠性。     

基于位移剩余的最优货物运输服务分析

基于需求主导原则，突出强调位移需求本身具有的独立价值，本文以位移价值与位移成本之差衡量货运需求主体的位移剩余。以位移剩余最大化为准则揭示货运需求主体选择运输服务方式的机理，并作为最优运输服务的标准。在位移价值测度方面，将货运需求按照时效性分为3类，基于需求主体的预期利益构建相应位移价值函数。在位移成本测度方面，通过对运输价格、运输时间、可靠性、便捷性及安全性等运输服务品质要素的量化，建立位移全过程的成本函数。联立位移价值与位移成本函数，以运输服务品质要素作为核心变量，构建基于位移剩余的最优运输服务分析模型。设置仿真算例，求取不同需求主体的位移剩余曲线，分析相对应的最优运输服务方式。结果显示：模型可基于异质性的位移需求有效分析最优运输服务，并可分析潜在运输需求转化为有效需求的条件，为企业及政府制定运输供给优化策略提供理论基础。     

Parameter optimization and parametric deviation influence for shock resistance of double-stage vibration isolation system with limiters北大核心CSCD

［Objectives］For marine nuclear power plants, the relative displacement of the pump supported by a vibration isolation system should be strictly restricted. In order to improve the shock resistance of a vibration isolation system with displacement limiters, the parameter optimization and parametric deviation influence are studied. ［Methods］The theoretical model of a double-stage vibration isolation system with typical limiter parameters is established, the analysis of the shock response characteristics of the system is carried out using the direct integration method, the optimal limiter parameters are obtained using a genetic algorithm, and the influence of parameter deviation on the shock resistance of the system is studied. ［Results］Limiter parameters significantly affect the shock response characteristics of the vibration isolation system. The optimal limiter parameters improve the shock resistance of the system, but parameter deviation has a great influence on shock resistance. Based on the influence of parameter deviation, a deviation control strategy is proposed in which the elastic parameter should have a positive deviation and the gap parameter a negative deviation. The simulation results show that the proposed strategy can effectively alleviate the shock resistance degradation caused by deviation.［Conclusions］The results of this study can be used to guide the design, manufacturing and variation control of limiters for vibration isolation systems. © 2022 Journal of Clinical Hepatology. All rights reserved.     

基于生产降本提效的船舶焊缝设计优化

为降低生产成本及提高施工效率,结合现有生产工艺的特点,通过研究入级船级社规范对焊缝设计的要求,考虑焊缝设计的经济性及可操作性,建立有效的焊缝设计优化工作机制,在详细设计阶段和生产设计阶段实现焊缝设计优化。优化的焊缝设计可充分利用现有资源,减少额外的生产投入,降低生产综合成本。将降低施焊难度及推广自动焊的设计理念融入焊缝设计中,在提高焊接效率的同时,产品焊缝的焊接质量特别是外观成形质量可得到保证,减少焊缝的补焊及打磨工作,提高产品的整体生产效率。     

模糊需求下快捷货物低碳运输方式及路径选择

针对模糊需求下的低碳快捷货运运输方式选择及路径规划问题,运用模糊优化理论,以2-型三角模糊变量表示不确定需求,以运输成本和碳排放量为目标,建立多目标模糊机会约束规划模型。采用逼近理想解排序法对多目标进行处理,得出不同置信水平下的快捷货物运输方案;进而探讨置信参数变化时对运输成本及碳排放量的影响,分析运输成本及碳排放量随运输时间的变化情况。研究结果表明:碳排放量对快捷货物运输方式及路径选择具有一定影响;需求不确定时,在满足运到时限的前提下,合理选择运输方式和路径对于降低运输成本和减少碳排放具有重要意义。     

基于SOC自适应分阶的动力锂电池两步优化快速充电策略

快速高效的充电方式对于推动汽车电动化,加快以石油为主导的传统交通能源向绿色低碳能源转型,实现中国"双碳战略"的目标具有重要意义。针对充电时间和充电损失的平衡优化问题,提出了一种基于SOC自适应分阶的两步优化多阶恒流充电策略。为实现充电过程的优化分阶,利用改进的二分K-means算法对基于内阻曲线的采样点集进行聚类,实现了充电区间关于内阻变化和分布特征的自适应划分。基于分阶优化结果,采用改进的非支配排序哈里斯鹰优化算法(INSHHO)求解优化电流对应帕累托前沿。利用Logistic混沌初始化及自适应t分布突变算子对哈里斯鹰模型(HHO)进行改进,进一步提升算法的全局寻优能力。最后通过充电对比试验,将优化多阶恒流充电策略与恒流恒压策略(CC-CV)和均分多阶恒流充电策略在不同充电时间条件下进行充电性能对比。结果表明:在充电时间保持一致的条件下,提出的优化多阶恒流充电策略较恒流恒压策略和均分多阶恒流充电策略的充电欧姆损失最大分别减少1.03%和0.3%;在温升表现上,优化多阶恒流充电策略较均分多阶恒流充电策略的充电温升最多降低了0.82℃。     

Minimizing lifetime structural costs: Optimizing for production and maintenance under service life uncertainty

Current naval shipowners are being forced to extend the service lives of their aging vessels from budgetary and political constraints. This is causing them to incur significant costs due to maintaining the structure of these older ships to keep the ships in operation. These increasing costs make it desirable to design new naval structures with their minimization in mind, as well as ensuring that such vessels are robust to changes in expected service life with respect to their total lifetime cost. However, such structures will necessarily have higher production costs, therefore, an optimization framework is presented to estimate both production and maintenance costs for a naval vessel's internal structure and develop trade-spaces between these two competing objectives in order to find designs that represent a balance of both.     

交通产业结构优化与城际铁路发展探讨

文章分析了城际高速铁路的特点和功能,阐述了交通产业结构的基本属性和发展趋势。并结合我国第一条城际铁路——京津城际铁路建成后对周边产业结构的实际影响效果,从交通产业结构优化的角度分析发展城际铁路的意义。     

Optimization-based assisted calibration of traffic simulation models

Use of traffic simulation has increased in recent decades; and this high-fidelity modelling, along with moving vehicle animation, has allowed transportation decisions to be made with better confidence. During this time, traffic engineers have been encouraged to embrace the process of calibration, in which steps are taken to reconcile simulated and field-observed performance. According to international surveys, experts, and conventional wisdom, existing (non-automated) methods of calibration have been difficult or inadequate. There has been extensive research on improved calibration methods, but many of these efforts have not produced the flexibility and practicality required by real-world engineers. With this in mind, a patent-pending (US 61/859,819) architecture for software-assisted calibration was developed to maximize practicality, flexibility, and ease-of-use. This architecture is called SASCO (i.e. Sensitivity Analysis, Self-Calibration, and Optimization). The original optimization method within SASCO was based on “directed brute force” (DBF) searching; performing exhaustive evaluation of alternatives in a discrete, user-defined search space. Simultaneous Perturbation Stochastic Approximation (SPSA) has also gained favor as an efficient method for optimizing computationally expensive, “black-box” traffic simulations, and was also implemented within SASCO. This paper uses synthetic and real-world case studies to assess the qualities of DBF and SPSA, so they can be applied in the right situations. SPSA was found to be the fastest method, which is important when calibrating numerous inputs, but DBF was more reliable. Additionally DBF was better than SPSA for sensitivity analysis, and for calibrating complex inputs. Regardless of which optimization method is selected, the SASCO architecture appears to offer a new and practice-ready level of calibration efficiency.     

C76系列敞车撑杆优化改进探讨

针对C₇₆系列敞车在运用过程中出现的撑杆脱落和折断故障进行了现场调研,分析了故障原因,并提出了将原焊接结构调整为螺栓连接结构的改进方案,实践证明该方案效果明显。