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。     

塞拉利昂Pepel地区淤泥质软土工程地质特性

根据塞拉利昂Pepel地区沿岸港口工程的地质勘察资料,通过对该区域淤泥质软土的物理、力学性质指标进行统计与分析,探讨Pepel地区淤泥质软土的工程地质特性,为该地区港口工程规划和水工建(构)筑物的设计提供必要参考。     

道路安全评价因子分析法

探讨了用因子分析法中公因子作为评价指标的替代指标,用其得分值作为新指标的数值.根据公因子对原始评价信息解释大小来计算新指标权重.然后,用线性加权法对评价对象的安全水平进行客观评价,最后,对此方法进行了比较应用研究,发现评价结论与其它方法有差别.     

权扰动的影响度量矩阵及其矩阵分析

对于加权线性回归模型,我们考虑权扰动的影响度量问题,给出权扰动的影响度量矩阵,利用迹、谱范数为工具,得出一些结论.     

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。     

沥青混凝土路面预防性养护效益计算及参数

路面预养护效益分析是路面预养护技术的核心,是比选预养护方案和确定实施时机的前提。根据美国等路面预养护效益分析的经验,结合我国公路养护技术水平,对沥青混凝土路面预养护效益分析中的效益指标、效益计算基线和预养护时间范围展开了讨论;进而,提出我国现阶段沥青混凝土路面预养护分析中效益指标选用建议和它们计算下基线的参考值,以及预养护时间范围的控制指标和控制标准的建议值。     

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。     

公共交通客运枢纽设计评价方法

公交客运枢纽是城市一体化交通系统的关键环节,目前国内在枢纽的设计和建设方面还存在诸多不足,科学合理地对枢纽设计方案进行评价显得尤为重要.本文从分析公交客运枢纽的设计原则和流程入手,讨论了公交客运枢纽设计方案的综合评价指标体系的确立,以及相关指标的量化,最后讨论采用灰色关联度的方法对方案进行评价.