Multi-objective bilevel construction material transportation scheduling in large-scale construction projects under a fuzzy random environment

Abstract

This paper investigates a transportation scheduling problem in large-scale construction projects under a fuzzy random environment. The problem is formulated as a fuzzy, random multi-objective bilevel optimization model where the construction company decides the transportation quantities from every source to every destination according to the criterion of minimizing total transportation cost and transportation time on the upper level, while the transportation agencies choose their transportation routes such that the total travel cost is minimized on the lower level. Specifically, we model both travel time and travel cost as triangular fuzzy random variables. Then the multi-objective bilevel adaptive particle swarm optimization algorithm is proposed to solve the model. Finally, a case study of transportation scheduling for the Shuibuya Hydropower Project in China is used as a real world example to demonstrate the practicality and efficiency of the optimization model and algorithm.     

Disruption Management of an Inequality-Based Multi-Fleet Airline Schedule by a Multi-Objective Genetic Algorithm

Abstract

This paper presents a novel application of a Method of Inequality-based Multi-objective Genetic Algorithm (MMGA) to generate an efficient time-effective multi-fleet aircraft routing algorithm in response to the schedule disruption of short-haul flights. It attempts to optimize objective functions involving ground turn-around times, flight connections, flight swaps, total flight delay time and a 30-minute maximum delay time of original schedules. The MMGA approach, which combines a traditional Genetic Algorithm (GA) with a multi-objective optimization method, can address multiple objectives at the same time, then explore the optimal solution. The airline schedule disruption management problem is traditionally solved by Operations Research (OR) techniques that always require a precise mathematical model. However, airline operations involve too many factors that must be considered dynamically, making a precise mathematical model difficult to define. Experimental results based on a real airline flight schedule demonstrate that the proposed method, Multi-objective Optimization Airline Disruption Management by GA, can recover the perturbation efficiently within a very short time. Our results further demonstrate that the application can yield high quality solutions quickly and, consequently, has potential to be employed as a real-time decision support tool for practical complex airline operations.     

一种永磁同步电机声品质主观评价方法研究

对永磁同步电机的稳态信号声品质进行了分析,并以声压级、响度、尖锐度、语音清晰度、波动度、粗糙度和音调度作为评价指标,建立了永磁同步电机声品质评价体系.采用分组成对比较法进行了主观评价,通过Bradley-Terry算法对评价结果进行了优化处理,分别搭建多元线性回归预测模型和MPGA-RBF预测模型,通过预留的检验样本对...     

基于LMS和SDP的发动机异响诊断方法研究

为有效提取发动机声信号特征,以诊断发动机的异响,提出了一种以最小均方算法和对称点图形算法相结合的发动机异响诊断方法。采用最小均方算法去除信号中的噪声,还原发动机声信号,而利用SDP图形技术将信号转换为极坐标图形,得以判断发动机是否产生异响。通过仿真与试验,验证了该方法的有效性。     

路面裂缝图像自动识别算法综述

路面裂缝自动检测对于路面养护管理、路面性能评价与预测、路面材料和结构设计具有重要的实用价值,但快速、准确、全面且稳定地识别路面裂缝一直是个难题.为此,对路面裂缝自动检测研究现状进行综述,包括以图像增强和去噪为目的的预处理方法,基于阈值分割、边缘检测和种子生长的空间域识别算法,以小波变换为代表的频域识别算法,基于有监督学习的识别算法及其他裂缝识别方法;指出既有裂缝识别算法存在易受光照和油污等因素的影响、裂缝识别图像连续性差和识别速度和精度较低等不足.最后,提出综合考虑边界和区域特征消除纹理和噪声干扰、基于局部和全局信息设计优化识别算法和基于三维图像进行裂缝识别等研究展望,为裂缝自动识别算法的改进提供参考.     

基于混合算法的大跨度斜拉桥可靠度评估

为研究大跨度顸应力混凝土(PC)斜拉桥的可靠度评估问题,提出了适用于大跨度PC斜拉桥这类复杂结构可靠性分析的混合算法.该方法综合运用了有限元分析(FEA)、径向基函数(RBF)神经网络、遗传算法(GA)和Monte Carlo重要抽样(MCIS)方法,并对算法中的关键步骤(RBF神经网络的初始样本点设计方法、MCIS的抽样中心点位置等)进行了改进,使结构分析模块与可靠度计算模块智能结合.利用数值算例的可靠度分析对该算法的有效性进行了验证.最后,以一座主跨为420 m的双塔PC斜拉桥为工程背景,进行了正常使用极限状态下的可靠度分析.参数分析表明:在汽车荷载作用下,该斜拉桥的主梁跨中位移超限失效概率比最长斜拉索强度失效概率高;汽车荷载的均值和标准差是影响斜拉桥可靠度的重要因素;随着汽车荷载均值系数的增大,主梁跨中位移超限失效的可靠指标下降的趋势较为显著.     

沉降引起的新旧箱梁刚接翼缘板内力简化算法

箱梁桥拓宽设计时,新旧桥基础差异沉降引起的刚接翼缘板内力是新板设计和旧板验算的前提.为研究该项内力的简化算法,以某连续箱梁桥拓宽工程为例,基于变形协调原理分析了新桥基础不均匀沉降全部工况下刚接翼缘板的变形,按上拱和下挠2种情况分别比较得到刚接翼缘板横向两侧相对位移的最大值,并偏安全地将其简化.以简化值为荷载,结合梁模式,针对桥梁纵向不同位置分别提出了沉降引起的刚接翼缘板内力的简化算法.最后将荷载简化值和简化算法的内力与三维实体有限元法的计算结果进行对比,验证了简化算法的可行性和计算精度.     

基于遗传算法的膜片弹簧的稳健化设计

在离合器膜片弹簧传统优化设计模型的基础上,应用工程稳健性的灵敏度分析,考虑了可控变量和不可控参数变差对膜片弹簧优化设计的影响,并采用遗传算法对目标函数进行了求解。结果表明,遗传算法具有比传统优化方法更强的全局寻优能力,稳健化设计能有效、可靠的减小质量波动对膜片弹簧优化设计的影响。     

波导中带帽圆柱壳的声辐射快速预报(英文)

In order to predict acoustic radiation from a structure in waveguide, a method based on wave superposition is proposed, in which the free-space Green's function is used to match the strength of equivalent sources. In addition, in order to neglect the effect of sound reflection from boundaries, necessary treatment is conducted, which makes the method more efficient. Moreover, this method is combined with the sound propagation algorithms to predict the sound radiated from a cylindrical shell in waveguide. Numerical simulations show the effect of how reflections can be neglected if the distance between the structure and the boundary exceeds the maximum linear dimension of the structure. It also shows that the reflection from the bottom of the waveguide can be approximated by plane wave conditionally. The proposed method is more robust and efficient in computation, which can be used to predict the acoustic radiation in waveguide.     

基于批量分割的虚拟单元制造系统多阶段动态调度

鉴于虚拟单元中批量分割调度模型研究的不足以及虚拟单元下批量分割呈现的新特点,文中考虑作业车间中同类设备有多台,多重作业具有不同加工路径可选的情况下的批量调度问题,其中批量分割包含横向分割和纵向分割。考虑到调度的复杂性,文中运用一个多阶段调度模型对设备资源进行分配,确定设备上的批量种类、大小和顺序,并在交货期内使总生产成本达到最小。通过算法对案例研究结果的对比,证明了所提方法的可行性和有效性。