调整涡轮通流特性提高增压机组与增压锅炉热力匹配性能

根据涡轮增压机组与增压锅炉匹配工作的基本原理,考虑两者之间存在的热平衡关系、压力平衡关系,以及配合约束边界条件,建立研究两者匹配工作特性的热力平衡计算模型,提出一种迭代求解计算方法。基于计算与测试数据的对比分析,证明建立模型的正确性和有效性。在此基础上,针对机组的联合工作线靠近压气机堵塞区域,可能影响机组满负荷长期工作性能,提出通过调整涡轮的通流特性以优化两者的热力匹配。计算结果表明,涡轮通流能力减小5%时,压气机工作线远离堵塞区域,效率得到提高,使涡轮做功能力增强,辅助汽轮机蒸汽消耗量减少30%,提高了两者的热力匹配性能。     

不同调制方式下甚低频发射天线系统效率研究

以MSK和OOK为例,通过分析码元速率、载频之间的相互变化关系,讨论在不同调制方式下的甚低频发射天线系统效率。给出不同调制方式下,天线系统辐射效率随天线系统带宽与码元速率比值的变化情况。     

基于广义回归神经网络的船舶交通量预测模型

船舶交通量受多种环境与社会因素的影响,使得船舶交通量预测存在复杂性与非线性的特点.在分析现有预测模型和方法不足的基础上,介绍了广义回归神经网络GRNN的基本原理与拓扑结构.不同类型船舶受各类因素影响的程度不同,根据天津港VTS(Vessel Traffic Services)中心提供的船舶交通量数据,按船舶种类将船舶交通量分为六类,利用GRNN神经网络分别进行预测.预测结果表明GRNN神经网络具有很强的非线性拟合能力,有效解决了天津港船舶交通量预测中的小样本问题,提高了整个预测系统的精度与稳定性.     

A static free-floating bike repositioning problem with multiple heterogeneous vehicles,multiple depots,and multiple visits

In this paper, a bike repositioning problem with multiple depots, multiple visits, and multiple heterogeneous vehicles for the free-floating bike-sharing system (FFBSS) is studied. Two types of nodes (i.e., easily and hardly access nodes) with different penalties are defined to represent different convenience levels of getting bikes from the FFBSS. The objective of the repositioning is to minimize the weighted sum of the inconvenience level of getting bikes from the system and the total unmet demand and the total operational time. To solve this problem, an enhanced version of chemical reaction optimization (CRO) is developed. A loading and unloading quantity adjustment procedure with the consideration of the node characteristics, including the type of node and its current state (i.e., in a balanced, surplus, or deficit state) is proposed and incorporated into this version to improve its solution quality. A concept of the nearby-node set is also proposed to narrow the search space. Numerical results are presented and indicate that compared to the traditional CRO and CPLEX, the enhanced CRO improves solution quality and has potential to tackle the repositioning problem for larger, longer repositioning duration, and more vehicle instances. The results also demonstrate the effectiveness of the proposed adjustment procedure.     

Airline crew pairing with fatigue: Modeling and analysis

Crew fatigue is one of the main causes of airline accidents. Regulatory authorities such as the Federal Aviation Agency constantly introduce new fatigue regulations, often in the form of hard constraints on the length of duty and rest periods. The complex nature of travel-related fatigue, however, makes it difficult to account for it indirectly through such constraints. Recent studies show that fatigue depends on human factors such as the homeostatic process and the circadian body clock as well as time-zone differences. In this work, we explicitly account for fatigue in crew pairing optimization through the Three Process Model of Alertness, one of the most comprehensive fatigue models available in the literature. We provide a mathematical model for the crew pairing problem that incorporates fatigue and solve it using a column generation approach. Numerical analysis on two real data sets reveals that the proposed approach is able to reduce the crew fatigue levels substantially with minimal impact on cost. In particular, it is shown that hard constraints on fatigue may still lead to high fatigue levels and that jet-lag and time-zone differences have a major impact. The results of the tests also show that some of the rules and regulations in practice may be omitted if the fatigue is accounted for directly.     

纯电动环卫车电驱动系统参数匹配研究

纯电动环卫车已成为城市日常生活的重要组成部分,为提高其动力性及作业效率,文章以一种基于平行轴变速箱与行星排集成的多模高效电驱动系统构型的纯电动环卫车为研究对象,首先对系统能够实现的模式进行了分析,其次以纯电动环卫车整车参数和动力性能为指标,分别匹配了驱动电机和作业电机峰值、额定功率、转矩及最高转速等参数,并搭建了整车动力学模型,通过仿真分析及系统台架进行爬坡和加速能力测试,证明系统参数匹配的有效性。     

城市轨道交通建设安全风险管理现状与发展建议

结合国内主要城市轨道交通建设安全风险管理开展情况，概括总结现行的管理模式及实施细节，分析安全风险体系建设、安全意识及保障能力、灾变机理、动态预警等方面存在的问题，阐述行业发展方向，相关成果可为建设管理者提升安全风险管理水平、保证工程安全质量提供借鉴。     

The fleet size and mix dial-a-ride problem with reconfigurable vehicle capacity

This paper introduces a fleet size and mix dial-a-ride problem with multiple passenger types and a heterogeneous fleet of reconfigurable vehicles. In this new variant of the dial-a-ride problem, en-route modifications of the vehicle’s inner configuration are allowed. The main consequence is that the vehicle capacity is defined by a set of configurations and the choice of vehicle configuration is associated with binary decision variables.The problem is modeled as a mixed-integer program derived from the model of the heterogeneous dial-a-ride problem. Vehicle reconfiguration is a lever to efficiently reduce transportation costs, but the number of passengers and vehicle fleet setting make this problem intractable for exact solution methods. A large neighborhood search metaheuristic combined with a set covering component with a reactive mechanism to automatically adjust its parameters is therefore proposed. The resulting framework is evaluated against benchmarks from the literature, used for similar routing problems. It is also applied to a real case, in the context of the transportation of disabled children from their home to medical centers in the city of Lyon, France.     

Integrated scheduling of m-truck,m-drone,and m-depot constrained by time-window,drop-pickup,and m-visit using constraint programming

The idea of deploying unmanned aerial vehicles, also known as drones, for final-mile delivery in logistics operations has vitalized this new research stream. One conceivable scenario of using a drone in conjunction with a traditional delivery truck to distribute parcels is discussed in earlier literature and termed the parallel drone scheduling traveling salesman problem (PDSTSP). This study extends the problem by considering two different types of drone tasks: drop and pickup. After a drone completes a drop, the drone can either fly back to depot to deliver the next parcels or fly directly to another customer for pickup. Integrated scheduling of multiple depots hosting a fleet of trucks and a fleet of drones is further studied to achieve an operational excellence. A vehicle that travels near the boundary of the coverage area might be more effective to serve customers that belong to the neighboring depot. This problem is uniquely modeled as an unrelated parallel machine scheduling with sequence dependent setup, precedence-relationship, and reentrant, which gives us a framework to effectively consider those operational challenges. A constraint programming approach is proposed and tested with problem instances of m-truck, m-drone, m-depot, and hundred-customer distributed across an 8-mile square region.     

The multi-port berth allocation problem with speed optimization and emission considerations

The container shipping industry faces many interrelated challenges and opportunities, as its role in the global trading system has become increasingly important over the last decades. On the one side, collaboration between port terminals and shipping liners can lead to costs savings and help achieve a sustainable supply chain, and on the other side, the optimization of operations and sailing times leads to reductions in bunker consumption and, thus, to fuel cost and air emissions reductions. To that effect, there is an increasing need to address the integration opportunities and environmental issues related to container shipping through optimization. This paper focuses on the well known Berth Allocation Problem (BAP), an optimization problem assigning berthing times and positions to vessels in container terminals. We introduce a novel mathematical formulation that extends the classical BAP to cover multiple ports in a shipping network under the assumption of strong cooperation between shipping lines and terminals. Speed is optimized on all sailing legs between ports, demonstrating the effect of speed optimization in reducing the total time of the operation, as well as total fuel consumption and emissions. Furthermore, the model implementation shows that an accurate speed discretization can result in far better economic and environmental results.