The load-dependent vehicle routing problem and its pick-up and delivery extension

The present paper examines a Vehicle Routing Problem (VRP) of major practical importance which is referred to as the Load-Dependent VRP (LDVRP). LDVRP is applicable for transportation activities where the weight of the transported cargo accounts for a significant part of the vehicle gross weight. Contrary to the basic VRP which calls for the minimization of the distance travelled, the LDVRP objective is aimed at minimizing the total product of the distance travelled and the gross weight carried along this distance. Thus, it is capable of producing sensible routing plans which take into account the variation of the cargo weight along the vehicle trips. The LDVRP objective is closely related to the total energy requirements of the vehicle fleet, making it a credible alternative when the environmental aspects of transportation activities are examined and optimized. A novel LDVRP extension which considers simultaneous pick-up and delivery service is introduced, formulated and solved for the first time. To deal with large-scale instances of the examined problems, we propose a local-search algorithm. Towards an efficient implementation, the local-search algorithm employs a computational scheme which calculates the complex weighted-distance objective changes in constant time. Solution results are presented for both problems on a variety of well-known test cases demonstrating the effectiveness of the proposed solution approach. The structure of the obtained LDVRP and VRP solutions is compared in pursuit of interesting conclusions on the relative suitability of the two routing models, when the decision maker must deal with the weighted distance objective. In addition, results of a branch-and-cut procedure for small-scale instances of the LDVRP with simultaneous pick-ups and deliveries are reported. Finally, extensive computational experiments have been performed to explore the managerial implications of three key problem characteristics, namely the deviation of customer demands, the cargo to tare weight ratio, as well as the size of the available vehicle fleet.     

Studying the benefits of carpooling in an urban area using automatic vehicle identification data

Carpooling has been considered a solution for alleviating traffic congestion and reducing air pollution in cities. However, the quantification of the benefits of large-scale carpooling in urban areas remains a challenge due to insufficient travel trajectory data. In this study, a trajectory reconstruction method is proposed to capture vehicle trajectories based on citywide license plate recognition (LPR) data. Then, the prospects of large-scale carpooling in an urban area under two scenarios, namely, all vehicle travel demands under real-time carpooling condition and commuter vehicle travel demands under long-term carpooling condition, are evaluated by solving an integer programming model based on an updated longest common subsequence (LCS) algorithm. A maximum weight non-bipartite matching algorithm is introduced to find the optimal solution for the proposed model. Finally, road network trip volume reduction and travel speed improvement are estimated to measure the traffic benefits attributed to carpooling. This study is applied to a dataset that contains millions of LPR data recorded in Langfang, China for 1 week. Results demonstrate that under the real-time carpooling condition, the total trip volumes for different carpooling comfort levels decrease by 32–49%, and the peak-hour travel speeds on most road segments increase by 5–40%. The long-term carpooling relationship among commuter vehicles can reduce commuter trips by an average of 30% and 24% in the morning and evening peak hours, respectively, during workdays. This study shows the application potential and promotes the development of this vehicle travel mode.     

基于灰色关联度的船舶风险控制方案多指标评价模型

分析了仅依靠成本效益评估而选择的船舶风险控制方案的片面性,综合考虑安全、环保、经济收益、成本等多因素对方案所表现的影响,建立了基于灰色关联度的船舶风险控制方案多指标评价模型。论文所建立的该模型可以充分利用各方案的指标取值所包含的信息,并考虑专家主观因素对指标重要度的影响,通过主客观综合赋权的方法突出某个指标在方案排序中的作用。以国际海事组织对液化天然气船的综合安全评估报告所提供的风险控制措施为例,使用该模型进行方案优选,并与仅用成本效益评估所得结果比较;分析比较表明:论文所建立的多指标评价模型可以更全面评估风险控制方案,方法合理,使用简便可靠。     

浅谈新双积分法规下乘用车降油耗方案研究

乘用车燃油经济性是评价车辆性能的重要指标,通常以在一定循环行驶试验工况下,行驶100km所消耗燃油升数(单位为L/100km)作为评价指标。影响乘用车燃油经济性的因素很多,文章以公司某在研SUV为例,通过仿真及转鼓油耗测试手段,在保证车辆驾驶体验体验前提下,研究如何降低整车燃油经济性。     

模糊模式识别在电器性能综合评估中的应用

采用了改进的模糊模式识别的方法,从综合考虑电磁电器产品性能的角度出发,将动态测得的能够反映电磁电器性能的主要特性指标,作为模糊模式识别的级别变量特征值,建立了综合评估电磁电器性能的模糊模式识别模型,并运用该方法对CJ20-100A交流接触器进行了综合评估,结果合理,方法可行,有一定的参考价值。     

地铁动车粘着系数的计算

为了较好地发挥车辆的牵引、制动性能,需要较合理地选择轮轨间粘着系数取值,从而使车辆处于较有利的粘着利用状况。从地铁列车的运行特点出发,提出电传动地铁动车计算粘着系数的计算要考虑大加、减速度的影响,并提出了具体的计算公式。     

围区吹填造地新型竹隔堤结构稳定性计算

采用竹结构替代传统的抛石与袋装砂堤,作为围区吹填分区隔堤是一个新的设计思路。为了解该新型隔堤挡土结构在土压作用下的整体安全稳定性与合理的结构尺度,基于浙江省台州东部新区涂面整理工程环湖护岸竹结构外部建设条件,分析影响其整体安全稳定性的因素,采用湖内蓄水平衡土压力的方法,进而运用有限元分析软件PLAXIS计算竹隔堤两侧不同水位差与竹隔堤结构不同跨数组合方案时竹隔堤整体稳定性。     

基于改进移动最小二乘法的结构可靠性分析

基于改进移动最小二乘法对结构可靠性问题进行分析,数值模拟结果表明,改进方法可有效提高计算精度.具体方法是使用椭圆范数代替二范数来度量样本点到中心点的距离,并根据上次迭代所得到的响应面在中心点处的法向量与坐标轴所成角度,对影响域进行旋转变换;从而将样本点的权重大小由样本点与中心点、响应面的距离共同决定,并将每次迭代得到的响应面函数在中心点处的法向信息包含在内.     

舰船消防投入消耗的重量和空间统计分析

战斗舰船上有众多的易燃易爆高发区域,必需设置舰船消防系统以达到防火和灭火的目的。但消防投入在提升舰船生命力与安全性水平的同时,也消耗了舰船有限的舱容和排水量。为了配合舰总体进行综合平衡,确保消防设计得以实施,对消防投入涉及的重量和空间进行统计分析,是有效支撑舰船总体布置和性能设计的重要途径。     

摆盘发动机空间机构的震动力完全平衡研究

特种摆盘发动机在航空航天、武器系统等方面有着广泛的应用。从空间机构学理论出发,抽象出机构模型,利用空间机构的通路定理,分析摆盘发动机机构震动力完全平衡的可行性,并推导出该空间机构必须满足的平衡条件;结合发动机自身结构特点,研究震动力完全平衡时各构件的结构条件与配重条件;同时针对所给条件的不足之处提出进一步的分析研究方法,为发动机在结构设计与减振方面提供理论基础。