基于计算机仿真的制造系统设施规划评价方法

传统的规划问题中只考虑了物料搬运和设备布置成本,而由于在制品(WIP)数量对物流系统,乃至整个生产系统性能有重要的影响,在进行规划设计时也应将其作为一个关键指标加以考虑.利用C#.Net平台编写的计算机仿真程序,可以容易地得到复杂生产系统包括WIP值在内的各项指标,为前期验证和比较各种不同规划方案、改进措施,进而寻找到更优的布局方案,提供了一种简单可行的方法.     

FL-26风洞扩散段结构优化分析

针对FL-26风洞原有结构（如扩散段）已出现裂纹,严重影响科研任务的按时完成以及风洞设备运行安全的问题,简介扩散段的结构,分析产生裂纹的原因;对原有结构进行详细的有限元验证计算和分析,得到裂纹产生的基本原因是其结构动态特性太差;基于改善动态特性的指标对多种方案进行比较,确立最终结构改造方案:更换内壳体,材料为16MnR...     

考虑车辆调度的周期性预防维修模型

维修中心对客户周期性的预防性维修通常只针对单设备进行优化,很少考虑维修车辆的调度问题,因此所得的方案往往不具有操作性.根据设备的故障规律,在研究合理的预防维修次数、维修间隔的前提下,充分考虑维修车辆的调度问题,对维修中心的成本因素进行分析并在满足设备可靠性的基础上建立了维修中心的成本最小化模型.通过仿真分析,得到最优的预防性维修次数,维修间隔和维修车辆路径,证明了模型的可行性和科学性,为维修中心的周期性预防维修提供决策支持.     

基于eM-Plant的焊接单元物流仿真与分析

制造单元规划设计的优劣对生产系统运行效率有显著影响,针对制造单元规划问题,本文利用eM-Plant对某企业焊接单元物流过程进行建模和仿真分析。通过模型运行仿真,得到物流评价参数、设备使用情况和工人工作情况,分析了设备的利用效率,并对存在的问题提出整改方案。     

基于SECI模型的网络数据挖掘系统优化设计

针对原有网络数据挖掘系统精准度低的问题,笔者提出基于SECI模型的网络数据挖掘系统优化设计。优化系统硬件中的网络数据采集器、网络数据预处理器等,提高了系统硬件设备的运行效率;在系统软件技术方面,以SECI模型为理论指导,在原有数据挖掘算法的基础上对其进行优化,提高了系统挖掘结果的精准度,以此实现了对网络数据挖掘系统的优化设计。经实验证明,优化后的系统挖掘结果的精准度得到了有效提高。     

基于eM—Plant的焊接单元物流仿真与分析

制造单元规划设计的优劣对生产系统运行效率有显著影响，针对制造单元规划问题，本文利用eM—Plant对某企业焊接单元物流过程进行建模和仿真分析。通过模型运行仿真，得到物流评价参数、设备使用情况和工人工作情况。分析了设备的利用效率。并对存在的问题提出整改方案。     

电力通信网络在运设备的多维健康评估模型研究

电力通信网络设备对于保证电网的安全和稳定运行具有重要作用.为此本文建立了电力通信设备的多维健康度评价模型,通过组合不同的评价指标对设备的运行状况进行评价,并通过对历史数据的分析得出各个评价指标的权重.结果表明本文提出的评估模型可以得出不同设备运行指标对设备健康状态评估结果的影响,同时得到不同种类设备的健康状态排序;算例...     

基于模型软件技术的火电仿真机虚拟DCS升级设计

结合目前火电厂普遍存在的集散控制系统升级的要求,对与之对应的火电厂仿真机的虚拟DCS进行升级.在最大程度保留原有模型的前提下,提出了基于模型技术的升级方案.由该方案实现的升级的仿真机保留原有的运行基本特性,同时又可对运行人员进行面向升级虚拟DCS的操作培训.     

石化企业蒸汽动力系统的多周期运行优化

为了满足石化企业工艺过程对蒸汽和电力不断变化的需要,实现企业降低成本、节能降耗的目的,必须保证蒸汽动力系统在最优状态下运行。本文针对这一问题建立了综合考虑设备启停费用的蒸汽动力系统多周期最优运行的混合整数线性规划模型,并将锅炉和汽轮机的模型进行了合理的线性化。该模型既保证了系统运行优化求解精度,又避免了非线性模型求解困难的问题,利用通用建模工具GAMS建模求解,并通过实例证明了利用本文建立的模型,在较短的时间内得到了最优的计划调度方案,并且节省了大量的运行成本。     

基于MVB的协议一致性测试系统设计

针对不同生产厂家的多功能车辆总线(Multifunction Vehicle Bus,MVB)设备存在兼容性和互操作性适应度差的问题,设计了基于MVB的协议一致性测试系统,给出了系统的总体结构、软硬件设计与实现方案,并构建测试集优化模型。测试系统的测试电路接口模块包括物理层接口模块和链路层接口模块两部分,负责将采集的MVB总线上的数据传递给控制与测试模块进行分析和处理。控制与测试模块软件部分着重设计了测试用例集优化模型,并采用高效的商业求解器CPLEX进行有效求解,提高了测试效率。实际运行结果表明:该测试系统是稳定并且高效的,可应用于不同MVB设备的协议一致性测试。     

Non-myopic vehicle and route selection in dynamic DARP with travel time and workload objectives

In dial-a-ride problems, a fleet of n vehicles is routed to transport people between pick-up and delivery locations. We consider an elementary version of the problem where trip requests arrive in time and require an immediate vehicle assignment (which triggers an appropriate route update of the selected vehicle). In this context, a relatively general objective can be stated as a weighted sum of the system's effort and the customers' inconvenience. However, optimizing almost any objective in this immensely complex stochastic system is prohibitively difficult. Thus the earlier work has largely resorted to heuristic cost functions that arise, e.g., from the corresponding static systems. By using the framework of Markov decision processes and the classical M/M/1 queue as a highly abstract model for a single vehicle, we explain why certain intuitive cost functions indeed give satisfactory results in the dynamic system, and also give an explicit interpretation of different components appearing in a general cost function. The resulting family of heuristic control policies is demonstrated to offer a desired type of performance thus justifying the assumed analogy between a multi-queue and dial-a-ride systems.     

A decision support system for the single-depot vehicle rescheduling problem

Disruptions in trips can prevent vehicles from executing their schedules as planned. Mechanical failures, accidents, and traffic congestion often hinder a vehicle schedule. When a vehicle on a scheduled trip breaks down, one or more vehicles need to be rescheduled to serve the passengers/cargo (if there are any) on that trip. The main objective of the vehicle rescheduling problem (VRSP) is to minimize operation and delay costs, while serving the passengers/cargo on the disrupted trip and completing all remaining trips that include the disrupted one. We report on a prototype decision support system (DSS) that recommends solutions for the single-depot rescheduling as well as vehicle scheduling (VSP) problems, since VRSP is closely related to VSP. The system was designed for human schedulers to obtain optimal vehicle assignments and reassignments. An experimental study, using randomly generated data, shows the efficiency of the developed algorithm. A real world problem, which involves the solid waste collection operational planning for a Brazilian city, is selected as the case study to illustrate the effectiveness of the developed DSS.     

Green vehicle routing in urban zones – A neuro-fuzzy approach

Local city authorities are making a serious effort to expand the number of low-greenhouse gas vehicles (green vehicles) at home. There is no reliable methodology, however, to support the implementation of this passenger transportation concept. In order to optimize the green capacity, a system has been developed to support decision making in urban green vehicle routing. The objective of this paper is to propose a green vehicle distribution model in a public transportation network. The problem has been defined as a problem of non-linear optimization with dispersed input parameters, requiring neuro-fuzzy logic. An adaptive neural network was developed, taking into account the costs to be borne by operators and users, and the environmental parameters along the observed vehicle route. Each input parameter of the neuro-fuzzy model has been placed in a complex context. They were divided into the elements describing in more detail the environmental status, the operator and passenger costs. The advantage of the model is that several factors shaping the input parameters have been taken into consideration. On the other hand, the complexity of urban systems management makes it a considerable challenge, and the surrounding circumstances are difficult to predict accurately. Accordingly, the inputs of the green vehicle model were fuzzified. The Index of Performance (IP) is the output, associated with each branch of the passenger transportation network. The model has been tested on a part of the public transport system in central Belgrade. The results have proven a practical application possible, and a calibration of input parameters allows for full implementation in public transport vehicle routing.     

基于巡逻无人机的轻量型安全帽佩戴检测方法与应用

目前,安全帽检测系统主要使用固定摄像头,无法实现全区域检测,而基于深度学习的检测算法结构复杂、计算成本高,无法满足移动端和嵌入式设备的部署要求。针对上述问题,该文提出一种基于无人机的安全帽轻量型视觉检测算法。系统通过无人机平台搭载的相机对施工现场进行图像采集,并无线传输至后台计算机进行处理,检测算法基于 YOLOv5s 框架进行了轻量化改进。针对无人机采集影像中目标占比较小的问题,该文采用了多尺度检测、图像预处理、正负样本不均衡等方法,对 YOLOv5s 目标检测算法进行针对性改进。测试结果表明,与原模型相比,轻量型目标检测模型的平均精度均值仅下降了 1.72%,但在同一 CPU 上的推理速度提升了 1 倍,浮点计算量由原来的每秒 165 亿次压缩至每秒 34 亿次,模型大小约为原模型的 1/10。     

A Multicommodity Integrated Freight Origin–destination Synthesis Model

This paper introduces a multi-commodity, single (generic) vehicle formulation of freight ODS model that combines a commodity-based model to estimate loaded truck trips and a complementary model of empty trips. This integration is important because explicit modeling of empty trips—that account for 30% to 40% of total truck trips—is required to avoid significant errors in the estimation of the directional traffic. The formulation is then applied to a case study. Two cases of the proposed model are studied. The first one uses total traffic in the estimation; while the second one is based on loaded and empty traffic. The results conclusively show that the models that consider an empty trip submodel significantly outperform the model that does not in their ability to replicate the observed traffic counts. The comparison between the results from the multi-commodity ODS and the single commodity ODS previously developed by the authors indicates that the multi-commodity formulation brings about substantial reductions in the error associated with the estimation of observed traffic counts. These reductions, in the order of 20% for empty traffic and 40% for loaded and total traffic, seem larger than the spurious improvement to be expected from the increased number of parameters, suggesting that the multi-commodity ODS formulation performs better. The results also show some minor improvements in the ability of the multi-commodity ODS formulation to estimate the OD matrices. In terms of the model's ability to correctly estimate the “true” value of the parameters of the models used, i.e., the parameter values estimated by calibrating the model directly from the OD data, it was found that the multicommodity ODS procedure is able to provide fairly good estimates Noortman and van Es's model parameters, though the parameters of the gravity models that came out to be quite different than the “true” values. The overall assessment of the formulation introduced here is that it represents a solid improvement with respect to comparable techniques.     

考虑时变速度的多车场绿色车辆路径模型及优化算法

针对多车场绿色车辆路径问题,根据顾客的坐标位置,采用K-means聚类方法将顾客分配给不同的车场;考虑时变速度和实时载重对车辆油耗和碳排放的影响,确定车辆油耗和碳排放的度量函数;在此基础上,以车辆油耗成本、碳排放成本、车辆使用成本、驾驶员工资以及时间窗惩罚成本之和最小化作为优化目标,构建多车场绿色车辆路径模型,并根据模...     

A game-theoretic approach to non-cooperative target assignment

In this paper, we have adopted a game-theoretic approach to consider the optimal assignment of targets to vehicles. We have taken optimality to mean the minimum sum of costs which are proportional to the Euclidean distance between a vehicle and its assigned target; this occurs when the set of targets is assigned to their nearest vehicles. In other words, each vehicle should assign itself to a target located within the Voronoi region associated with the vehicle. Standard schemes require communication between vehicles at least to rank the targets according to the nearest-neighbour rule. In our proposed model, there is no need for communication among the vehicles, and only limited communication between the targets and the vehicles is required. Specifically, we have introduced an appropriate utility function which depends on the distance between the vehicles and targets and the number of vehicles engaging a particular target. The vehicles negotiate their choice of targets via regret matching. We present simulations which demonstrate that vehicles select targets that fall within their Voronoi region. Vehicles that do not have any targets within their Voronoi region select their nearest unassigned target. We also present a communication model illustrating how the model can be implemented in a practical scenario.     

Modelling peak-hour urban freight movements with limited data availability

Modelling the complexity of urban freight transport requires large amounts of data related to supply chain management, delivery practices, tour configuration, time windows, etc., but when all this detailed data is not available local authorities still need models that represent this type of transport and its contribution to congestion and environmental impacts. We present here an improvement on other recent works, consisting of a demand model for B2B and home deliveries during the morning peak hour that uses only very limited data to estimate the number of delivery vehicles entering and leaving each zone of the city. We then calculate the trip distribution using an entropy maximisation approach, and solve the resulting model using simulated annealing. We apply this model to a case study in the city of Seville, in Spain, and compare its results to those produced by a gravity model, and with actual traffic counts.     

Group-based protocol and mobility model for VANETs to offer internet access

Some public transport vehicles embed devices that allow passengers to connect to Internet while traveling. These vehicles are true mobile Internet access zones inside public paths. These zones could be used by other vehicles moving close to them in order to have Internet access. At the same time, other vehicles in the influence area could be used as relay nodes which would increase this access area. In this paper, we present a group-based protocol and mobility model for vehicular ad hoc networks (VANETs) where each public transport vehicle forms a group of vehicles. They can access and allow access to Internet though the public transport vehicle. Each vehicle is moving inside the group and can leave and join any group at will, while all groups are moving. First, we will show the algorithm and protocol to achieve our purpose. Then, we will study the probability of having Internet access in order to demonstrate that it is a feasible proposal. Finally, we simulate a study case based on real values in order to obtain the performance of our proposal in terms of several network parameters such as the number of hops per route, the network traffic, the page response time, network delay, network load and so on.     

基于智能垃圾桶的垃圾分类动态收运路径优化问题研究

针对城市生活垃圾分类收运过程中存在的环境二次污染和垃圾产生量不确定性等问题,提出了一种基于智能垃圾桶的动态收运车辆路径优化方法。建立以最小化碳排放成本、燃油消耗成本、固定成本和车辆延迟到达惩罚成本为目标的动态车辆路径优化模型。采用滚动时域的方式将动态问题转换为一系列静态问题,并设计两阶段算法进行求解。首先采用粒子群算法对收运车辆路径进行规划,而后在每个时域末,综合考虑待清运垃圾桶的位置和垃圾量、垃圾收运车辆的位置和装载量以动态调整现有车辆路径。研究结果表明,相较于传统的静态收运方案,动态垃圾收运方案能够在降低车辆运输成本和碳排放成本的同时,显著降低由于清运不及时造成的环境二次污染的风险。