Order-first split-second methods for vehicle routing problems: A review

Cluster-first route-second methods like the sweep heuristic (Gillett and Miller, 1974) are well known in vehicle routing. They determine clusters of customers compatible with vehicle capacity and solve a traveling salesman problem for each cluster. The opposite approach, called route-first cluster-second, builds a giant tour covering all customers and splits it into feasible trips. Cited as a curiosity for a long time but lacking numerical evaluation, this technique has nevertheless led to successful metaheuristics for various vehicle routing problems in the last decade. As many implementations consider an ordering of customers instead of building a giant tour, we propose in this paper the more general name of ordering-first split-second methods. This article shows how this approach can be declined for different vehicle routing problems and reviews the associated literature, with more than 70 references.     

适用于我国Ⅲ、Ⅳ级铁路的列控系统

我国Ⅲ、Ⅳ级铁路有配备列控系统的需求.ITCS和ERTMS Regional是适合Ⅲ、Ⅳ级铁路的2种列控系统,介绍了它们的结构和功能特点.     

构建科学的员工绩效管理体系探讨

文章针对当前国有企业绩效管理中常见问题,分析存在问题的原因,并结合企业绩效管理实践,提出建立和改善绩效管理体系的对策和建议。     

Modeling the Car-Truck Interaction in a System-Optimal Dynamic Traffic Assignment Model

Several transportation problems, such as implementation of truck-only lanes, require understanding the interaction of heterogeneous dynamic traffic flows in order to provide accurate solutions. System-optimal dynamic traffic assignment can be modeled using a network loading procedure based on the cell transmission model, that is, the hydrodynamic wave model, and solved by linear programming. However, this framework cannot handle the asymmetric integration between the flow of trucks and cars. This article presents a novel formulation for network loading in system-optimal dynamic traffic assignment considering car–truck interactions. By using an embedded cell transmission model, this formulation incorporates a set of assumptions related to the kinematic characteristics of the flow of cars, trucks, and their interactions that can be solved using linear programming. We present numerical results supporting our modeling assumptions. Likewise, the observed emergent behavior captures the car–truck interactions accurately and indicates that minimum system-optimal travel time is obtained by encouraging cars to use highways with shorter distances.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Vehicle restrictions and CO2 emissions in Beijing – A simple projection using available data

The Beijing Government launched a new policy on restricting vehicle ownership in late 2010 to regulate the faster motorization and the excessive vehicular carbon dioxide (CO₂) emissions. In this paper, we first analyzed this policy and its effect on private passenger vehicle population. The private passenger vehicle population in Beijing from 2011 to 2020 was predicted under three different scenarios: no constraint (NC), current constraint (CC) and tighter constraint (TC). Then the assessment of vehicular emissions reduction benefits was made on the basis of private passenger vehicle population, vehicle kilometers traveled and CO₂ emission factors. It was projected that the CO₂ emissions in 2020 will reach 23.90, 15.55 and 13.23 million tons under NC, CC and TC respectively. The policy is very effective in controlling the faster motorization and reducing CO₂ emissions.     

Controlled mechanical vibration applied to driver’s right heel to sustain alertness: Effects on cardiovascular behavior

Vehicle-related countermeasures to sustain driver’s alertness might improve traffic safety. The purpose of this study was to investigate the effects of somatosensory 20 Hz mechanical vibration, applied to driver’s right heel during prolonged, simulated, monotonous driving, on their cardiovascular hemodynamic behavior. In 12 healthy young male volunteers, during 90-min periods of simulated monotonous driving, we compared cardiovascular variables during application of 20 Hz mechanical vibration with 1.5 Hz as a control and with no vibration. The parameters recorded were indices of key cardiovascular hemodynamic phenomena, i.e., blood pressure as an indicator of stress, cardiac output, and total peripheral-vascular resistance. The principle results were that all conditions increased the mean blood pressure, and elicited a vascular-dominant reaction pattern typically observed in monotonous driving tasks. However, mean blood pressure and total peripheral-vascular resistance during the monotonous task were significantly decreased in those receiving the 20 Hz vibration as compared with 1.5 Hz and with no vibration. The observed differences indicate the cardiovascular system being more relieved from monotonous driving stress with the 20 Hz vibration. The major conclusion is that applying 20 Hz mechanical vibration to the right heel during long-distance driving in non-sleepy drivers could facilitate more physiologically appropriate status for vehicle operation and could be a potential vehicular countermeasure technology.     

翻车机牵车驱动装置优化改造

针对翻车机牵车驱动装置在设计上存在问题,从机械结构和电气控制上进行了分析,并相应地进行了优化改造,使之更合理,消除了故障隐患。     

爆胎汽车整车运动分析及控制

通过轮胎试验得到GT175/60 R14轮胎在正常胎压及零胎压下的力学特性参数,以此为依据,运用CarS im软件对爆胎汽车进行整车动力学仿真,找出汽车偏航原因,分析驾驶员不同操作所引起的整车运动性能变化以及汽车稳定性控制系统对爆胎汽车的影响。仿真结果表明,稳定性控制系统对于减轻爆胎带来的后果具有积极的作用。     

基于非参数回归的快速路行程速度短期预测算法

基于北京市快速路上的检测器所采集的历史数据，经过数据筛选，剔除判别，小波滤噪平稳处理，聚类分析等过程，建立了交通状态演变系列的历史样本数据库。基于所构建的历史数据库，通过数值试验，确定了状态向量、距离匹配原则，K近邻值等参量，构建了一种基于K近邻的非参数回归短时交通预测模型，实现了对路段行程速度的短时预测。最后，利用随机选取的历史数据系列对预测模型的精度进行了检验。结果表明，预测算法的精度可以达到90％以上，可以很好地满足ITS应用系统对于交通预测数据的精度要求。