感应加热电源并联控制系统的通信设计与实现

基于西门子S7-200 SMART PLC和DSP处理器,设计了感应加热电源并联控制系统,建立了DSP和PLC之间、PLC与触摸屏HMI之间的通信协议并编写程序,实现了DSP与PLC之间的数据传输。实际应用表明:该系统通信效果良好,具有较强的实用价值。     

考虑均衡性的城市轨道交通线路负荷水平评估研究

线路负荷水平的评价工作是优化运输组织方案的重要前提。首先，本文分析了采用单一均值性指标表征负荷水平不能体现线路内负荷分布偏差的问题。为此，从城市轨道交通线路客流与运输能力匹配的角度出发，以列车负荷为评价单元，建立包括负荷均值和标准差率二维指标的线路负荷水平评估模型。负荷均值指标考虑了各评价单元加权计算，以反映每个评价单元对线路负荷水平的贡献程度，标准差率指标表征负荷均衡性。模型分析得出，线路所有区间的运力同等规模变化不影响标准差率指标，相对提高大客流区间或大客流方向上的输送能力能够改善线路负荷的均衡性。算例分析表明：客流方向不均衡系数超过 1.4 时，应考虑运力优化措施以提高运输能力利用的均衡；组织列车大小交路方案和不成对行车模式，能够提高线路负荷的均衡程度。     

浅谈滚动物料计划在汽车行业中的应用

随着汽车逐年普及,消费者需求多样化、个性化随着增长,而且消费者对提车周期要求越来越高。汽车生产企业如何快速、高效的占领市场,同时降低供应链物流成本,是目前自主品牌汽车企业面临重大挑战。需要从软硬件进行全面提升竞争能力,物料组织改进是整个汽车供应链改进不可缺少的一个重要环节,能帮助企业迅速占领市场,以最小的成本换取最大利润,全面降低整个物流运营成本。     

铁路枢纽小运转列车径路优化

以枢纽小运转列车运营成本和货运站装卸费用最小为目标,考虑载重量、列车数和运行时间约束,建立了枢纽小运转列车路径优化模型.并以某铁路枢纽地区为例,运用ILOG CPLEX优化软件仿真求解,得出枢纽小运转列车的最优路径方案.实例证明模型是有效可行的,与实际运行比较,优化后的费用降低近5%,运输距离缩短近8.31%.     

基于Intergraph Smart 3D的邮轮电缆自动敷设功能优化开发

Intergraph Smart 3D软件的电缆敷设功能在化工电力行业应用较为广泛,考虑到邮轮电气生产设计中的电缆具有长度长(3 000 km～5 000 km)、种类多、通道网络复杂和分段敷设的特点,直接应用Smart 3D原生的电缆敷设功能进行电缆敷设存在较大的风险。从邮轮电缆敷设需求出发,对Smart 3D原生电缆敷设解决方案进行优化,充分考虑电气设计人员的使用习惯,基于贪心算法和单源最短路径算法(Dijkstra算法)优化算法解决断续托架的电缆敷设和电缆分区敷设最优路径选取的问题,提高电气设计人员的电缆敷设效率。     

基于遗传算法的道路车辆自组织网络源路由机制

在当前基于交叉路口的城市车辆自组织网络(VANETs)路由协议中，道路上数据包传输大多采用基于地理位置的贪婪转发策略，当数据量较大时，个别节点负载较重，极易引起传输延迟增大乃至丢包的情况.本文提出了一种基于遗传算法的源路由机制，通过记录单体车辆的驾驶信息而非传统方法中的车流均值数据，来预测道路上车辆网络的连通情况，并借助遗传算法，首次基于道路连通性、节点负载和连接跳数这3 点综合考虑，计算得出道路上最佳的源路由节点序列.仿真实验结果表明，在传输率与延迟时间上，性能均优于传统的贪婪路由机制，尤其在车流量为250 veh· lane-1· h-1时，传输率提升约13%.该研究可为智能交通信息通讯提供可靠助力.     

Benefit of speed reduction for ships in different weather conditions

Currently, the shipping industry is facing a great challenge of reducing emissions. Reducing ship speeds will reduce the emissions in the immediate future with no additional infrastructure. However, a detailed investigation is required to verify the claim that a 10% speed reduction would lead to 19% fuel savings (Faber et al., 2012).This paper investigates fuel savings due to speed reduction using detailed modeling of ship performance. Three container ships, two bulk carriers, and one tanker, representative of the shipping fleet, have been designed. Voyages have been simulated by modeling calm water resistance, wave resistance, propulsion efficiency, and engine limits. Six ships have been simulated in various weather conditions at different speeds. Potential fuel savings have been estimated for a range of speed reductions in realistic weather.It is concluded that the common assumption of cubic speed-power relation can cause a significant error in the estimation of bunker consumption. Simulations in different seasons have revealed that fuel savings due to speed reduction are highly weather dependent. Therefore, a simple way to include the effect of weather in shipping transport models has been proposed.Speed reduction can lead to an increase in the number of ships to fulfill the transport demand. Therefore, the emission reduction potential of speed reduction strategy, after accounting for the additional ships, has been studied. Surprisingly, when the speed is reduced by 30%, fuel savings vary from 2% to 45% depending on ship type, size and weather conditions. Fuel savings further reduce when the auxiliary engines are considered.     

A hybrid optimization-simulation approach for robust weekly aircraft routing and retiming

We address the robust weekly aircraft routing and retiming problem, which requires determining weekly schedules for a heterogeneous fleet that maximizes the aircraft on-time performance, minimizes the total delay, and minimizes the number of delayed passengers. The fleet is required to serve a set of flights having known departure time windows while satisfying maintenance constraints. All flights are subject to random delays that may propagate through the network. We propose to solve this problem using a hybrid optimization-simulation approach based on a novel mixed-integer nonlinear programming model for the robust weekly aircraft maintenance routing problem. For this model, we provide an equivalent mixed-integer linear programming formulation that can be solved using a commercial solver. Furthermore, we describe a Monte-Carlo-based procedure for sequentially adjusting the flight departure times. We perform an extensive computational study using instances obtained from a major international airline, having up to 3387 flights and 164 aircraft, which demonstrates the efficacy of the proposed approach. Using the simulation software SimAir to assess the robustness of the solutions produced by our approach in comparison with that for the original solutions implemented by the airline, we found that on-time performance was improved by 9.8–16.0%, cumulative delay was reduced by 25.4–33.1%, and the number of delayed passengers was reduced by 8.2–51.6%.     

Improving maritime inventory routing: application to a Brazilian petroleum case

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.     

Generalized Maximum Benefit Multiple Chinese Postman Problem

This research is focused on a generalization on the Max Benefit Chinese Postman Problem and the multiple vehicle variant of the Chinese Postman Problem. We call this generalization, the Generalized Maximum Benefit k-Chinese Postman Problem (GB k-CPP). We present a novel Mixed Integer Programming (MIP) formulation for the GB k-CPP. Four different cases of the model are discussed. The first case, performs arc-routing with profits and assumes that the origin and destination for each vehicle is the same for each cycle and is given by the user. The next case relaxes the assumption that the origin and destination for each vehicle should be the same and allows the users to select possible origins/destinations for vehicles. Case three gets the origin for each vehicle as input and produces a solution based on finding the best destination for each vehicle. The last case, that is very general, allows the optimization model to select possibly different locations for vehicle origin and destination, during each cycle. The different cases are applied to a security patrolling case conducted on the network of University of Maryland at College Park campus and the results are compared.