基于交路单元的高速铁路乘务交路编制模型与算法

为了解决高速铁路列车乘务计划编制过程中的乘务交路自动化生成问题,从工作实际的角度出发,首先提出以交路单元作为列车乘务交路编制基本单位的方法,在此基础上建立以最小费用为目标的乘务交路编制优化模型,在该模型中对异车体换乘的接续时间进行区分。然后,针对该模型特点,对基于贪婪思想的启发式算法进行求解。最后,以京津城际铁路北京南站至天津站间的列车数据对该算法进行了验证。计算结果表明,用该方法编制的最小费用乘务交路在值乘时长和换乘次数方面能够体现出较好的均衡性。     

城市公交出行系统中最优路线算法研究

公交出行最优路线算法主要以距离为标准,在得出了换乘方案之后,可以进一步地考虑时间因素．从而找到更具优胜性的换乘方案,但这还有待于进一步的探讨、研究。     

基于改进遗传算法的物流配送点选址问题研究

在已知物流配送点数目的条件下,以最低送货运输费用为目标,利用最小二乘法推导出多物流配送点的选址模型及其迭代算法;根据遗传算法的基本思想,设计了求解已知物流配送点数目条件下的选址和物流服务分配问题的遗传算法.通过实例证明该模型及算法具有较好的应用价值.     

A New Arithmetic Coding System Combining Source Channel Coding and MAP Decoding

A new arithmetic coding system combining source channel coding and maximum a posteriori decoding were proposed. It combines source coding and error correction tasks into one unified process by introducing an adaptive forbidden symbol. The proposed system achieves fixed length code words by adaptively adjusting the probability of the forbidden symbol and adding tail digits of variable length. The corresponding improved MAP decoding metric was derived. The proposed system can improve the performance. Simulations were performed on AWGN channels with various noise levels by using both hard and soft decision with BPSK modulation.The results show its performance is slightly better than that of our adaptive arithmetic error correcting coding system using a forbidden symbol.     

An Enhanced NEH Method in Solving Permutation Flow Shop Problem

This paper proposed an enhanced NEH with full insertion moves to solve the permutation flow shop problem.The characteristics of the original NEH are investigated and analyzed,and it is concluded that the given method would be promising to find better solutions,while the cost would be increased.Fast makespan calculating method and eliminating non-promising permutation policy are introduced to reduce the evaluation effort.The former decreases the time complexity from O(n4m) to O(n3m),which is an acceptable cost for medium and small size instances considering the obtained solution quality.The results from computational experience show that the latter also can eliminate a lot of non-promising solutions.     

树枝形铁路专用线取送车作业模型及启发式算法

合理安排铁路专用线取送车顺序,有利于提高调车机车作业效率、加速货车周转。以调车机车完成一批调车作业任务后所走行路程最短为优化目标;为便于区分,增设虚拟车站,并以各装卸作业点和车站为顶点;以根据作业情况不同调整后的作业点间距离为线段权,建立树枝形专用线取送车作业的哈密尔顿图模型,指出合理的取送车顺序为满足所有优先权关系的哈密尔顿回路。设计启发式算法进行求解,以不同作业的起点为始点,顺或逆时针确定机车下一访问作业点,从而形成不同的初始解,采用局部交换作业顺序规则对目前解进行改进,选择机车走行路程最短的路径为满意解。其他作业形式可认为是送调取结合作业形式的简化形式,所提出的模型及算法同样适用。     

具有旋转约束的启发式装箱算法

主要研究在有限旋转约束下的装箱问题。以Pisinger树搜索启发装箱算法为基础,在货物装配过程中考虑实际可行的旋转约束限制;并通过对树搜索宽度和深度的合理限制,使算法具有满意的运算时间;在装箱结果中,通过对货物层以及货物条的位置调整,从而满足重心位置和左右平衡等约束而不影响既有的装箱率。试验结果表明旋转约束对于装箱性能有一定的影响,但是改进算法在满足各种实际约束的条件下仍具有良好的装箱性能,同时该算法具有合理的运算时间。     

铁路机车司机驾驶能力的心理学检验指标及其效标

应用检验空军驾驶能力的心理学指标——五项纸笔方法对铁路机车司机驾驶能力进行心理学检验，并用标准９分制进行校标，结果表明除曲线轨迹相关较差不宜应用外，其他四项均可应用。     

A hybrid scheme for real‐time prediction of bus trajectories

The uncertainty associated with public transport services can be partially counteracted by developing real‐time models to predict downstream service conditions. In this study, a hybrid approach for predicting bus trajectories by integrating multiple predictors is proposed. The prediction model combines schedule, instantaneous and historical data. The contribution of each predictor as well as values of respective parameters is estimated by minimizing the prediction error using a linear regression heuristic. The hybrid method was applied to five bus routes in Stockholm, Sweden, and Brisbane, Australia. The results indicate that the hybrid method consistently outperforms the timetable and delay conservation prediction method for different route layouts, passenger demands and operation practices. Model validation confirms model transferability and real‐time applicability. Generating more accurate predictions can help service users adjust their travel plans and service providers to deploy proactive management and control strategies to mitigate the negative effects of service disturbances. Copyright © 2017 John Wiley & Sons, Ltd.     

A case study of Beijing bus crew scheduling: a variable neighborhood‐based approach

Crew scheduling for bus drivers in large bus agencies is known to be a time‐consuming and cumbersome problem in transit operations planning. This paper investigates a new meta‐heuristics approach for solving real‐world bus‐driver scheduling problems. The drivers' work is represented as a series of successive pieces of work with time windows, and a variable neighborhood search (VNS) algorithm is employed to solve the problem of driver scheduling. Examination of the modeling procedure developed is performed by a case study of two depots of the Beijing Public Transport Group, one of the largest transit companies in the world. The results show that a VNS‐based algorithm can reduce total driver costs by up to 18.1%, implying that the VNS algorithm may be regarded as a good optimization technique to solve the bus‐driver scheduling problem. Copyright © 2015 John Wiley & Sons, Ltd.