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.     

Assigning fighter plane formations to enemy aircraft using fuzzy logic

Fighter aircraft protect specific facilities on alert in the air by patrolling expectation zones. These zones are located in the direction from which enemy aircraft attacks are expected; fighter formations are sent from them to intercept enemy aircraft. The problem considered in this paper is to determine the optimum assignment of fighter plane formations to enemy formations. The proposed solution is based on fuzzy logic and integer linear programming. A numerical example is given to illustrate the application possibilities of the proposed solution.     

Future electricity demand from battery‐powered vehicles

An important decision faced by airline schedulers is how to adapt the flight schedule and aircraft assignment to unforeseen perturbations in an established schedule. In the face of unforeseen aircraft delays, schedulers have to decide which flights to delay, and when delays become excessive, which to cancel. Current scheduling models deal with simple decision problems of delay or cancellation, but not with both simultaneously. But in practice the optimal decision may involve results from the integration of both flight cancellations and delays. In Part I of this paper, a quadratic programming model for the integration decision problem is given. The model can formulate the integration of flight cancellations and delays as well as some special cases, such as the ferrying of surplus aircraft and the possibility of swapping different types of aircraft. In this paper, based on the special structure of the model, an effective algorithm is presented, sufficient computational experiments are conducted and some results are reported. These show that we can expect to obtain a sufficiently good solution in terms of reasonable CPU time.     

基于双层规划模型的地下综合管廊PPP项目入廊定价研究

为解决地下综合管廊项目PPP模式运作过程中存在的入廊定价难的突出问题,首先,基于现阶段入廊价格管制的需要以及各参与方在入廊定价决策过程中的主从递阶结构特点,决定利用双层规划模型研究PPP模式下地下综合管廊项目的入廊定价问题,将政府方作为定价决策的上层,社会资本方和管线单位作为决策的下层,建立政府、社会资本方与管线单位分别以社会福利最大化、预期收益最大化和保留效用最大化为目标的双层规划模型,以期求解得到令三方满意的入廊费、日常维护费与补贴额度。然后,以延安市地下综合管廊PPP项目为例,检验模型与求解方法的可行性。最后,基于研究结论提出加强顶层设计、强化价格监管、建立动态调价机制的合理化建议。