基于有限元法及遗传算法的推力杆球铰多目标优化方法

为优化推力杆的球铰结构并提高其疲劳寿命,提出一种基于有限元法和遗传算法的推力杆球铰多目标优化方法。该优化方法通过有限元法计算不同橡胶衬套预压缩量和球铰结构的推力杆球铰橡胶衬套的应变分布特征和刚度参数,进而得到推力杆刚度参数、橡胶衬套预压缩量与球铰关键结构参数之间的关系,并在此基础上采用遗传算法建立推力杆球铰的多目标优化模型。利用建立的多目标优化模型计算得到推力杆球铰的优化方案。样件台架试验结果表明,此优化方案使推力杆球铰的疲劳寿命提高了7倍。提出的多目标优化方法充实了变截面橡胶金属复合结构的设计理论,并为推力杆的优化设计提供了理论依据。     

基于粒子群优化反步法的船舶航向控制器设计

考虑到反步法在随机干扰下具有较优的控制效果,利用反步法设计基于Nomoto模型的船舶航向控制器;设计一种基于粒子群优化(Particle Swarm Optimization,PSO)反步法的航向控制器,其能通过优化不确定增益参数来消除部分冗余控制。通过仿真试验比较不同航向控制器的性能。仿真结果表明:粒子群优化反步法航向控制器具有更高的控制精度和更强的鲁棒性。     

A joint bottom-up solution methodology for system-level pavement rehabilitation and reconstruction

We present a methodology for the joint optimization of rehabilitation and reconstruction activities for heterogeneous pavement systems under multiple budget constraints. The proposed bottom-up approach adopts an augmented condition state to account for the history-dependent properties of pavement deterioration, and solves for steady-state policies for an infinite horizon. Genetic algorithms (GAs) are implemented in the system-level optimization based on segment-specific optimization results. The complexity of the proposed algorithm is polynomial in the size of the system and the policy-related parameters. We provide graphical presentations of the optimal solutions for various budget situations. As a case study, a subset of California’s highway system is analyzed. The case study results demonstrate the economic benefit of a combined rehabilitation and reconstruction budget compared to separate budgets.     

基于克里金模型的潜水器耐压舱结构优化

本文研究Kriging建模和序贯加点相结合的方法,用于解决目标函数或者约束函数无法显式表达下的优化问题。在加点准则中为了避免出现龙格现象,改进了加点优化时步长要求,在优化过程中融入多种群遗传算法提高了序贯加点值的计算准确性。计算结果表明,改进后的加点准则在存在多区域或者多个极值点的情况下均可快速搜索到最优点位置。建立了载人潜水器载人舱以重量为优化目标,以强度要求为约束的球壳厚度优化模型,采用此方法在初始选取5个样本取样,序贯加点6个样本点,计算得到球壳的最优厚度值为50.5569 mm,可有效指导设计工作。     

Achieving sustainable development of supply chain by incorporating various carbon regulatory mechanisms

Nowadays, sustainability issues have received considerable attention in supply chain management because of the governmental requirements as well as expectations of the people. This paper introduces a novel supply chain network design problem to cover three dimensions of sustainability, namely economic, environmental, and social. The advantage of the presented model stems from considering the booming development aligned with reduction in environmental impact. In this paper, to achieve the mentioned benefits and to derive a more sustainable supply chain, a novel model in the presence of the most commonly used carbon policies is proposed. This paper, addresses sustainable development through imposing proper carbon regulatory mechanisms. Main contribution of this study is to consider the effect of imposing carbon policies on environmental advantages as well as improving the regional development level in a supply chain network design problem. Moreover, the shipment consolidation decisions are utilized to reduce cost as well as environmental impact. In addition, a novel mixed uncertainty approach is proposed to capture the uncertain emission parameters. The numerical examples and a case study are analyzed to evaluate the performance of the proposed models. It is concluded that, a high-growth economy with low-carbon can be made and also almost global well-being of people is ensured by applying the proposed model. Some managerial insights are provided for the enterprises of supply chains to make the most appropriate sustainable decisions. Finally, proper carbon emission policies are suggested based on the region sustainability characteristics.     

三维物探船稳性优化设计

三维物探船因上层建筑面积大、重心位置高,其稳性问题是设计过程中需解决的重要问题。文章以国内首艘完全自主设计的6缆三维物探调查船为例,介绍其稳性优化设计方面的经验。首先对三维物探调查船的特点进行介绍;然后介绍总体布置优化、空船重量重心的控制对稳性的影响;最后分别就完整稳性和破舱稳性的计算特点及优化方法进行分析。该文总结了三维物探调查船的稳性特点和注意事项,为今后设计工作提供指导。     

基于条件生成对抗网络的扇区复杂度评估

扇区复杂度作为管制员工作负荷和动态空域配置的重要参考依据，需要事先准确地对其 进行评估。本文针对有监督复杂度数据集存在的小样本问题，提出基于条件生成对抗网络的扇 区复杂度评估框架。首先，构建交通流量、航空器性能和潜在冲突这3类复杂度指标，并结合主观 复杂度等级得到标定样本；其次，利用条件生成对抗网络设计有标记样本生成算法，获得增广数 据集；最后，分别采用逻辑回归、支持向量机和随机森林算法建立复杂度评估模型。以中南区域 扇区为例，从定性和定量的视角验证生成样本的有效性，并在多种训练集配置下对比各模型评估 结果。研究结果表明：条件生成对抗网络在200次迭代后逐步收敛至稳定；生成样本与真实样本 的绝大多数指标在均值上的相对误差小于5%，在标准差上的相对误差大于5%；在多分类评价指 标下，增广数据集对3种模型整体评估精度分别提升11.77%、11.04%和8.34%。本文提出的评估 框架可以在有限数据条件下提高样本多样性，是解决扇区复杂度评估问题的一种有效方法。     

“上软下硬”复合地层地连墙快速成槽施工关键技术研究

针对上软下硬地层条件下地连墙施工经验相对匮乏的现状,以杭州某地铁车站"上软下硬"复合地层地连墙施工为工程背景,以不增加工程造价为前提,对地下入岩连续墙施工快速施工技术开展研究。通过"优化地下入岩连续墙施工机械配套选型,提高成槽质量及效率"、"改进护壁泥浆配比,确保护壁效果"、"研发改造成槽施工机械,减少涡流对上部软土层的影响"等多方面工作,优化传统入岩地连墙成槽工艺,形成了一套"旋挖钻机配合方锤破碎岩层、成槽机取土"的快速成槽工艺,有效确保车站地连墙施工进度及质量,可为日后类似工程提供经验借鉴。     

基于新型液冷板的电池热管理系统多目标优化

为提升电池热管理系统(BTMS)散热效果,采用计算流体力学(CFD)和基于快速非支配排序遗传算法(NGSA-II)的多目标优化相结合的方法设计优化了一种新型液冷板模型。通过电池实验,得到不同放电倍率下单体电池产热量。以通道夹角、通道宽度、冷却液的质量流量为设计变量,平均温度、温度标准差和压降为目标函数,采用拉丁超立方体抽样(LHS)方法,在设计空间中选取了35个设计点,利用响应面近似模型(RSM)拟合出目标函数的表达式。结果表明:在5C放电倍率下,优化后液冷板的散热性能得到有效提升,与初始模型相比,液冷板的平均温度和温度标准差分别下降了11%、51.2%,压降仅增加了3.3Pa。     

Robust optimization of distance-based tolls in a network considering stochastic day to day dynamics

This paper investigates the nonlinear distance-based congestion pricing in a network considering stochastic day-to-day dynamics. After an implementation/adjustment of a congestion pricing scheme, the network flows in a certain period of days are not on an equilibrium state, thus it is problematic to take the equilibrium-based indexes as the pricing objective. Therefore, the concept of robust optimization is taken for the congestion toll determination problem, which takes into account the network performance of each day. First, a minimax model which minimizes the maximum regret on each day is proposed. Taking as a constraint of the minimax model, a path-based day to day dynamics model under stochastic user equilibrium (SUE) constraints is discussed in this paper. It is difficult to solve this minimax model by exact algorithms because of the implicity of the flow map function. Hence, a two-phase artificial bee colony algorithm is developed to solve the proposed minimax regret model, of which the first phase solves the minimal expected total travel cost for each day and the second phase handles the minimax robust optimization problem. Finally, a numerical example is conducted to validate the proposed models and methods.