基于时间窗和最低排空要求的集装箱空箱调运优化研究

空箱调运是解决铁路车站集装箱装卸不均问题的关键,现有研究多从优化调运成本出发,未考虑最低排空需求。在考虑软时间窗造成的费用并定义站间最低排空要求的基础上,构建基于多种箱型的集装箱空箱调运双层规划模型,将空箱调运分为以满足最大排空要求为目的调运和以效益最大为目的的调运,并设计相应的求解算法。研究结果表明,配流方法求得的最佳效益值为Cplex求得最佳效益值的97.75%,并且为满足最低排空要求付出的效益损失代价与时间窗内的单位库存费用与机会损失费用呈负相关。     

带时间窗约束的集装箱空箱调运随机机会约束模型研究

集装箱空箱调运是集装箱运输中的重要环节。现实中集装箱需求和供给具有不确定性,需求方对集装箱运达时刻上有时间窗的约束。基于此,提出了基于运达时间约束的集装箱空箱随机机会模型。首先确定了空箱供给和需求的随机变量,然后构建了集装箱随机到达时间约束的满意度函数,最后分别将集装箱运输费用和到达时刻满意度作为优化目标,建立了集装箱空箱调运双目标随机机会约束模型,并设计了基于TOPSIS的限定参数区间搜索算法。算例表明,与供需确定的情况相比,所建立模型的集装箱空箱调运费用节省了6.2%,运达时刻满意度提高了16.5%,验证了模型的有效性。     

基于技术站中转作业的集装箱空箱调配模型

在传统以空车走行里程最少为目标的铁路空车调整模型基础上,提出基于技术站中转作业的集装箱空箱调配模型,根据前提假设构建模型,并给出模型求解步骤,通过算例分析,利用计算机软件得到最优空箱流分配方案.     

铁路空车调整综合优化模型

随着铁路运输的发展,货物车辆供给不足的问题日益突出。为在路网上合理调拨空车,根据空车走行费用(含中转费用),以及空车过早(或过晚)到达需求站而产生的额外管理费(或推迟运输的延误费)之和最小的原则,同时考虑线路的通过能力,建立了铁路空车调整综合优化模型,并用LINGO语言对模型进行了求解。     

铁路集装箱空箱调运最优化方案研究

在分析铁路集装箱空箱调运存在问题的基础上，运用线性双层规划理论，以运输成本最小和托运人满意度最大为目标，建立铁路集装箱空箱调运最优化模型，并通过实例检验模型的优化效果，以降低运营成本、提高集装箱使用效率。     

铁路重载运输车流组织与编组站改编能力优化方法研究

重点考查既有线能力释放引发运量增长的情况下,重载运输因素对车流组织方案及编组站改编能力配置的影响。通过设置不同的增长系数模拟不同的运量涨势,构建了考虑重载因素的铁路车流组织与编组站改编能力联合优化模型,并利用变异的蚁群算法实现模型的求解,准确测算编组站的改编能力扩充需求。研究发现,在运量增长的条件下重载和非重载直达去向的数量会逐渐增加,编组站的改编能力配置与车流组织方案密切相关、一变俱变,改编能力的扩充需求不会随着运量的增加而持续增长,在确定实际方案时需要综合考虑近、远期的发展需要。     

铁路省际煤炭调运的格局及优化

铁路煤炭运输在煤炭运输中占主导地位,影响着煤炭的供需平衡。在对我国铁路省际煤炭调运格局进行分析的基础上,构建了铁路省际煤炭调运的优化模型,并进行优化分析。研究表明:2001—2010年我国铁路煤炭运输量增长率低于煤炭生产增长率,铁路运输在各省煤炭调运中发挥着不同的作用;优化后的铁路省际煤炭调运成本比优化前节约了82.2亿元,平均运输距离缩短了98.3 km,各供给地和需求地的铁路煤炭流向和流量进行了重新分配。     

基于改进点-弧模型的铁路网车流径路优化模型研究

车流径路优化对于均衡利用各个车站和区间的能力,降低车流运输费用,提高铁路运营效益具有重大的意义。为了更好地规划设计铁路网车流径路,阐述车流径路优化研究现状,针对点-弧模型的缺陷,遵循车流不拆散原理,在满足弧的能力约束、节点流量守恒约束的情况下,以车流总走行费用最小为目标函数,构建基于改进点-弧模型的铁路网车辆径路优化模型,采用Lingo软件求解。以我国东北地区局部铁路网为例进行分析,实验结果表明,模型可以准确地求得总车流运输费用最低的各支车流的径路,具备有效性和合理性,为铁路网车流径路优化提供理论依据。     

陆路集卡运输中空箱调运问题创新模式研究

随着港口腹地对外贸易量的增加，腹地地区的集装箱量也不断增多，陆路集卡运输成本也成为了一个增加运输成本的重要因素之一。针对一些主要从事陆路运输的中小型企业而言甚至是关乎企业兴衰的主要问题之一，对一些大型企业而言也使得成本压力不断增大，所以如何解决陆路集卡运输中的空箱调运问题已经变得十分紧迫和重要。     

铁路集装箱空箱运输成本分析

根据铁路运输企业2004年财务结算的有关规定,对中铁集装箱运输有限责任公司2004年向提供服务的铁路局支付的各相关费用情况进行了分析,9项付费支出共占公司总支出的81.67%。其中铁路空箱运输量占总运输量的21.9%,付费支出占总付费的7.97%。为此提出加强成本意识,强化市场营销,优化运输组织等减少空箱运输的建议措施。     

基于快铁融合的上海铁路集装箱快运站选址研究

快铁融合可以充分发挥快递企业和铁路运输的优势,有效提升物流作业效率,达到运输资源分配平衡的效果,是多元化运输的发展方向。在既有和计划建设的铁路货运站中选择铁路集装箱快运站与快递企业集散网络衔接,以快递企业时间满意度和集散运输成本为目标,构建基于时间满意度的铁路集装箱快运站选址模型,以上海铁路集装箱快运站为例进行实证分析,提出保证铁路集装箱快运站与快递企业合理衔接的对策,为铁路集装箱运输融入快递市场提供决策支持,加速快铁融合的实施。     

Multi-port vs. Hub-and-Spoke port calls by containerships

This paper addresses the design of container liner shipping networks taking into consideration container management issues including empty container repositioning. We examine two typical service networks with different ship sizes: multi-port calling by conventional ship size and hub-and-spoke by mega-ship. The entire solution process is performed in two phases: the service network design and container distribution. A wide variety of numerical experiments are conducted for the Asia–Europe and Asia–North America trade lanes. In most scenarios the multi-port calling is superior in terms of total cost, while the hub-and-spoke is more advantageous in the European trade for a costly shipping company.     

铁路集装箱场区安全布局评价研究

铁路集装箱场区的布局在体现基本运输功能和满足生产工艺要求的基础上，要综合考虑其各种安全因素。通过分析铁路集装箱场区安全布局的内外部影响因素，建立安全布局的综合评价指标体系，采用基于Rough Set的算法进行综合评价。通过算例对铁路集装箱场区的布局进行综合评价，结果证明了算法的实用性和可行性。     

Operational shadow pricing in back haul container shipping

Minimum acceptable rates for back haul cargo are difficult for carriers to establish in practice. They depend on complex factors such as availability of empty containers in the vicinity, cost of repositioning empties and container on-hiring decisions. A shadow pricing and “shadow credit” approach is proposed and applied to an inland network. Such a model can help carriers undertake yield management at the operational level to improve financial performance in a post-conference era. Results also suggest a positive relationship between variability in the imbalance situation of laden containers in a particular trade and volatility of short-term back haul freight rates.     

Terminal and yard allocation problem for a container transshipment hub with multiple terminals

This paper presents an integer programming model for the terminal and yard allocation problem in a large container transshipment hub with multiple terminals. The model integrates two decisions: terminal allocation for vessels and yard allocation for transshipment container movements within a terminal as well as between terminals. The objective function aims to minimize the total inter-terminal and intra-terminal handling costs generated by transshipment flows. To solve the problem, we develop a 2-level heuristic algorithm to obtain high quality solutions in an efficient way. Computational experiments show the effectiveness of the proposed approach.     

A maritime container repositioning yield-based optimization model with uncertain upsurge demand

The role of container repositioning has become more important under the severe cargo shipping environment, affected by world trade growth, trade imbalance, slow steaming strategy and high container manufacturing cost. Low cost, better routing, and supplying equipment to higher yield cargo become the top criteria. A yield-based container repositioning framework is developed, followed by a constrained linear programming optimizing the container repositioning from surplus to deficit locations. The model incorporated change of destinations of empty containers and adjustment factors handling upsurge demand. The model is applied to optimize daily container repositioning operations with a better route, costs and equipment supply.     

A reactive tabu search algorithm for the multi-depot container truck transportation problem

A container truck transportation problem that involves multiple depots with time windows at both origins and destinations, including the reposition of empty containers, is formulated as a multi-traveling salesman problem with time windows (m-TSPTW) with multiple depots. Since the problem is NP-hard, a cluster method and a reactive tabu search (RTS) algorithm are developed to solve the problem. The two methods are compared with the mixed integer program which can be used to find optimum solutions for small size problems. The computational results show that the developed methods, particularly the RTS algorithm, can be efficiently used to solve the problem.     

The simultaneous berth and quay crane allocation problem

This paper addresses efficient berth and crane allocation scheduling at a multi-user container terminal. First, we introduce a formulation for the simultaneous berth and crane allocation problem. Next, by employing genetic algorithm we develop a heuristic to find an approximate solution for the problem. The fitness value of a chromosome is obtained by crane transfer scheduling across berths, which is determined by a maximum flow problem-based algorithm based on a berth allocation problem solution defined by the chromosome. The results of numerical experiments show that the proposed heuristic is applicable to solve this difficult but essential terminal operation problem.     

A heuristic algorithm for yard truck scheduling and storage allocation problems

The yard truck scheduling and the storage allocation are two important decision problems affecting the efficiency of container terminal operations. This paper proposes a novel approach that integrates these two problems into a whole. The objective is to minimize the weighted sum of total delay of requests and the total travel time of yard trucks. Due to the intractability of the proposed problem, a hybrid insertion algorithm is designed for effective problem solutions. Computational experiments are conducted to examine the key factors of the problem and the performance of the proposed heuristic algorithm.