集装箱物流收益管理的能力分配模型

提出了研究不确定环境下集装箱物流收益管理的框架．针对集装箱物流收益管理系统的核心问题——运输能力分配，建立了考虑整条航线多个港口需求不确定性的舱位分配随机规划模型，并介绍了用机会约束规划方法求解模型的步骤．通过实例数值仿真，证明了该模型的可行性，并揭示了船舶承载能力对需求较大的航段的舱位分配策略影响较大，而需求的波动对舱位分配策略也有较大影响．     

信息不对称下交通运输管理中的最优激励

应用信息经济学的委托代理理论,将政府作为委托人,交通运输管理人员作为代理人,研究了在委托人对代理人的能力水平有不完全信息的逆向选择和在管理活动中代理人的努力程度等行为不可能跟踪监督的道德风险同时存在的广义委托代理中的最优激励机制.通过建立非线性规划的数学模型,获得了在风险中性的委托人为具有"勤能补拙"特征的风险厌恶的代理人设计的最优激励工资合同的混同均衡的显式解,混同的工资合同解释了岗位工资的合理性和激励作用.     

信号控制模型中利益分配问题的研究

设计了一个平衡约束条件下信号控制与平衡网络设计组合问题的多目标规划模型，然后使用效用函数法将有双目标的上层优化问题转化为一个单目标优化问题．在这种情况下，该模型变成一个标准的双层规划模型。并利用全局优化方法模拟退火算法和惩罚函数法相结合求解．     

A network optimization-based approach for crowd management in large public gatherings

Effective crowd management during large public gatherings is necessary to enable pedestrians' access to and from the venue and to ensure their safety. This paper proposes a network optimization-based methodology to support such efficient crowd movement during large events. Specifically, a bi-level integer program is presented that, at the upper-level, seeks a reconfiguration of the physical layout that will minimize total travel time incurred by system users (e.g. evacuees) given utility maximizing route decisions that are taken by individuals in response to physical offerings in terms of infrastructure at the lower-level. The lower-level formulation seeks a pure-strategy Nash equilibrium that respects collective behavior in crowds. A Multi-start Tabu Search with Sequential Quadratic Programming procedure is proposed for its solution. Numerical experiments on a hypothetical network were conducted to illustrate the proposed solution methodology and the insights it provides.     

基于交通约束的城市最佳用地结构模糊规划模型研究

提出了基于交通系统容量约束的城市土地使用模糊规划模型.该模型以最大开发强度为目标,以交通总生成量不超过路网交通容量为约束条件,确定土地使用优化结构.作为城市规划分析模型中的1个子模型,该模型已在城市的总体规划中得到应用.规划实践表明,模型具有重要的理论价值和较强的可操作性.     

考虑临时和预约需求的共享泊位动态分配方法

为解决多居住区共享停车场同时存在临时共享停车需求和提前预约共享停车需求的动态泊位分配问题，本文提出将未来几个时段的共享停车供需同时考虑到当前时段泊位分配中的单时段泊位分配方法，并将本时段泊位匹配结果延伸到后续时段，从而提出共享泊位动态分配流程。对临时停车需求，以用户成本最小为目标确立优先泊位匹配的原则；对预约停车需求，以系统收益最大为目标确立在当前时段结束时统一分配泊位的原则。定义4个指标评价模型效果。 选择来源于成都市某共享停车APP的3个居住小区一天的数据，对模型进行实证研究以及灵敏度分析。研究结果表明：临时共享停车需求和提前预约共享停车需求所占比例在0.4~0.6时，泊位分配后总目标表现最好；将未来几个时段的供需同时考虑到当前时段中，泊位分配效果更好，且考虑的未来时段越多，泊位分配后总目标越好；在泊位分配时，为了较好地保证临时停车需求能够优先分配到泊位，往往会造成总目标变差。     

智能车经济性起步车速规划研究

智能车的车速决策影响燃油经济性。以起步阶段加速工况的燃油经济性为优化目标,建立了瞬态燃油消耗模型,并提出了基于该模型的经济性换挡规律制定方法;根据车辆纵向动力学方程,建立了基于前向欧拉离散方法的车速状态转移方程,以及确定相应的初末约束条件、边界条件;基于动态规划最优性原理,提出了智能车起步过程的经济性车速规划方法,建立了基于速度状态搜索策略;根据Matlab/Simulink和CarSim联合仿真,对比了典型驾驶员速度跟随模式的燃油消耗水平,结果表明,基于动态规划优化后的经济性车速及相应的挡位序列具有良好的节油特性,可为智能车经济驾驶的车速规划及挡位规划提供指导。     

A bi-objective bi-level signal control policy for transport of hazardous materials in urban road networks

A bi-objective bi-level signal control optimization for hazardous material (hazmat) transport is considered to assess trade-offs between travel cost and environment impacts such as public risk exposure. A least maxi-sum risk model with explicit signal delay is presented to determine generalized travel cost for hazmat carriers. Since the bi-level signal control problem is generally a non-convex program, a bundle method using generalized gradients is proposed. A bounding strategy is developed to stabilize solutions of the bi-level program and reduce relative gaps between iterations. Numerical comparisons are made with other risk-averse models. The results indicate that the proposed bi-objective bi-level model becomes even amiable to signal control policy makers since provides flexible solutions whilst is acceptable to carriers since takes account of travel delay at signal-controlled junctions. Moreover, the trade-offs between public risk and generalized travel costs are empirically investigated among different risk models with a variety of weights. As a result, the proposed model consistently exhibits highly considerable advantage on mitigation of public risk whilst incurred less cost loss as compared to other alternatives.     

An integrated programming model for storage management and vehicle scheduling at container terminals

In this paper, we study the optimization of yard operations, which are critical for the terminal efficiency. A linear mixed integer programming (MIP) model is proposed for scheduling different types of equipment and planning the storage strategy in an integrated way. We also investigate a nonlinear mixed integer programming (NLMIP) model to reduce the number of constraints and the computational time. A set of numerical results are carried out for the comparison between the linear model and the nonlinear model. Finally, we propose a genetic algorithm for the MIP model to illustrate how large scale problems can be solved and to show the effect of different factors on the performances of the optimization model.     

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.