基于时间便利性的行程选择

出行者基于广义成本最小化选择最佳的出行方式。广义成本包含资金成本、时间成本与舒适成本。随着社会的发展。出行者对时间成本看的越来越重。时间成本与时间长度和时间起始点有关,时间成本不仅包含出行者的时间价值也包括早到或晚到的损失。相对于频率较快的地铁与公交,满足乘客长距离出行的火车的时间点对乘客出行的影响很大。本文通过对杭州与上海之间的城际高铁后,出行者在汽车、自驾车及高铁三种方式之间的选择进行调查。得出列车行程安排应考虑旅行时间长度来安排起讫点的时间点,并通过两个例子来佐证合理的时间安排可增加列车的竞争力。优化出行结构同时也保证了列车的客源。本文的研究对于其他的城际列车有借鉴作用。     

三峡水库航运优化调度蓄水方案研究

文章通过研究分析水库蓄水过程对坝上下游河段演变的影响,并根据汛末长江来水过程,对三峡枢纽汛末蓄水的起蓄时间、起蓄水位及下泄流量进行了研究,提出了合理的优化调度方案。该方案可降低三峡枢纽汛末蓄水对坝上回水变动区河段淤积的不利影响．提高对坝下河段浅滩的冲刷效果,并保证三峡水库按时蓄满。     

Scheduling for Uncertain Data Broadcast in Mobile Networks

With the increasing popularity of wireless sensor network and GPS (global positioning system) , uncertain data as a new type of data brings a new challenge for the traditional data processing methods. Data broadcast is an effective means for data dissemination in mobile networks. In this paper, the definition of the mean uncertainty ratio of data is presented and a broadcasting scheme is proposed for uncertain data dissemination. Simulation results show that the scheme can reduce the uncertainty of the broadcasted uncertain data effectively at the cost of a minor increase in data access time, in the case of no transmission error and presence of transmission errors. As a result, lower uncertainty of data benefits the qualities of the query results based on the data.     

基于蚁群算法的航班着陆排序

当空中交通拥挤时，对航班的着陆顺序进行的调整，可以缓解拥挤，减少航班延误，提高飞行安全性，本文将蚁群算法用于着陆航班的排序问题，首先，建立以航班延误总时间最小为目标的规划模型，将航班着陆排序问题转化为非对称的TSP问题；然后，用蚁群算法寻找符合实际操作的优化排列；最后，经过对某机场实际数据的仿真计算，并与实际运行相比较，本文应用的算法具有较好的有效性和较强的使用性。     

朔黄铁路调度优化系统研究

为提高轴重300 k N以上重载铁路运输效率,建立基于车-地连续通信的调度优化系统,通过对历史运行数据进行充分的分析计算,得出优化的列车运行计划,并实时监督列车的运行状况,优化行车密度,实时调整运行计划,从而优化列车运行策略,提高效益。     

The time slot allocation problem under uncertain capacity

This paper presents two stochastic programming models for the allocation of time slots over a network of airports. The proposed models address three key issues. First, they provide an optimization tool to allocate time slots, which takes several operational aspects and airline preferences into account; second, they execute the process on a network of airports; and third they explicitly include uncertainty. To the best of our knowledge, these are the first models for time slot allocation to consider both the stochastic nature of capacity reductions and the problem’s network structure. From a practical viewpoint, the proposed models provide important insights for the allocation of time slots. Specifically, they highlight the tradeoff between the schedule/request discrepancies, i.e., the time difference between allocated time slots and airline requests, and operational delays. Increasing schedule/request discrepancies enables a reduction in operational delays. Moreover, the models are computationally viable. A set of realistic test instances that consider the scheduling of four calendar days on different European airport networks has been solved within reasonable – for the application’s context – computation times. In one of our test instances, we were able to reduce the sum of schedule/request discrepancies and operational delays by up to 58%. This work provides slot coordinators with a valuable decision making tool, and it indicates that the proposed approach is very promising and may lead to relevant monetary savings for airlines and aircraft operators.     

The flight perturbation problem

Airlines spend considerable time, effort and financial resources on planning. It is essential to create a competitive timetable and construct a fleet and a crew schedule that utilizes these resources to the maximum. Unfortunately, it is all too common that an airline is faced with the necessity of reconstructing their schedules due to some unforeseen event, for example an aircraft breakdown or a crew member that is indisposed. In this paper, an application that can help airlines solve the complex problem of reconstructing aircraft schedules is presented. A mixed integer multicommodity flow model with side constraints is developed and further reformulated into a set packing model using the Dantzig—Wolfe decomposition. Cancellations, delays and aircraft swaps are used to resolve the perturbation, and the model ensures that the schedule returns to normal within a certain time. Two column generation schemes for heuristically solving the model are tested on real problem data obtained from a Swedish domestic airline. The computational tests show that the application is capable of presenting high quality solutions in a few seconds and therefore can be used as a dynamic decision support tool by the airlines.     

CO2 efficiency in road freight transportation: Status quo, measures and potential

Road freight transport continues to grow in Germany and generates 6% of the country’s CO₂ emissions. In logistics, many decisions influence the energy efficiency of trucks, but causalities are not well understood. Little work has been done on quantifying the potential for further CO₂ reduction and the effect of specific activities, such as introducing computer assisted scheduling systems to trucking firms. A survey was survey out and linked fuel consumption to transport performance parameters in 50 German haulage companies during 2003. Emission efficiency ranged from 0.8 tonne-km to 26 tonne-km for 1 kg CO₂ emissions. The results show potential for improvements given a low level of vehicle usage and load factor levels, scarce use of lightweight vehicle design, poorly selected vehicles and a high proportion of empty runs. IT-based scheduling systems with telematic application for data communication, positioning and navigation show positive effects on efficiency. Fuel use and transport performance was measured before and after the introduction of these systems.     

Plan-based flexible bus bridging operation strategy

Bus bridging has been widely used to connect stations affected by metro disruptions such that stranded passengers could resume their journeys. Previous studies generally assumed that a bus operates exclusively on one bridging route with given frequency, which limits the service flexibility and reduce the operational efficiency. We propose a strategy to instruct buses to operate on predefined bridging routes once they are dispatched from depots. Buses are allowed to flexibly serve different bridging routes. Each bus operates based on a bridging plan that lists the stations to serve in sequence instead of route frequencies. A two-stage model is developed to optimize the bridging plans and their assignments to buses with the objectives that balance the operational priorities between minimizing bus bridging time and reducing passenger delay. A Weight Shortest Processing Time first (WSPT) rule based heuristic algorithm is developed to solve the proposed model. The developed model is further incorporated in a rolling horizon framework to handle dynamic passenger arrivals during the disruption period. The effectiveness of the proposed strategy is demonstrated in comparison with alternative strategies in real-world case studies.     

混沌微粒群算法在离散型生产调度中的应用

本文基于离散型生产调度问题的定义、约束条件,建立了相应的数学模型,针对微粒群算法后期容易陷入局部最优解且收敛速度慢的特点,提出了混沌的微粒群算法.详细介绍了混沌微粒群算法在离散型生产调度的优化流程,并将该算法用于实际项目,进行优化求解,与基本的微粒群算法对比得出更好的结果,验证了混沌微粒群算法的优越性.