Dynamic traffic metering in urban street networks: Formulation and solution algorithm

Traffic metering offers great potential to reduce congestion and enhance network performance in oversaturated urban street networks. This paper presents an optimization program for dynamic traffic metering in urban street networks based on the Cell Transmission Model (CTM). We have formulated the problem as a Mixed-Integer Linear Program (MILP) capable of metering traffic at network gates with given signal timing parameters at signalized intersections. Due to the complexities of the MILP model, we have developed a novel and efficient solution approach that solves the problem by converting the MILP to a linear program and several CTM simulation runs. The solution algorithm is applied to two case studies under different conditions. The proposed solution technique finds solutions that have a maximum gap of 1% of the true optimal solution and guarantee the maximum throughput by keeping some vehicles at network gates and only allowing enough vehicles to enter the network to prevent gridlocks. This is confirmed by comparing the case studies with and without traffic metering. The results in an adapted real-world case study network show that traffic metering can increase network throughput by 4.9–38.9% and enhance network performance.     

Towards data-driven car-following models

Car following models have been studied with many diverse approaches for decades. Nowadays, technological advances have significantly improved our traffic data collection capabilities. Conventional car following models rely on mathematical formulas and are derived from traffic flow theory; a property that often makes them more restrictive. On the other hand, data-driven approaches are more flexible and allow the incorporation of additional information to the model; however, they may not provide as much insight into traffic flow theory as the traditional models. In this research, an innovative methodological framework based on a data-driven approach is proposed for the estimation of car-following models, suitable for incorporation into microscopic traffic simulation models. An existing technique, i.e. locally weighted regression (loess), is defined through an optimization problem and is employed in a novel way. The proposed methodology is demonstrated using data collected from a sequence of instrumented vehicles in Naples, Italy. Gipps’ model, one of the most extensively used car-following models, is calibrated against the same data and used as a reference benchmark. Optimization issues are raised in both cases. The obtained results suggest that data-driven car-following models could be a promising research direction.     

Wheat interchanges in Europe: Transport optimization reduces emissions

Numerous Life Cycle Analysis of bread pointed out that wheat production and transportation have important impacts on the environment. But wheat is grown all around the world and it is not always consumed where it is produced. In this paper an analysis of the wheat movements around Europe is done, taking special attention on the Spanish situation. An optimization of wheat exchanges is done eliminating the import–export overlapping. This optimization entails a reduction of the number of trips by 34% and the CO₂ emissions reduction due to transportation is calculated to be 121.175 tones. Consequently less trips, fewer trucks, less traffic and lower emissions that brings economic, social and environmental benefits.     

Solving the gate assignment problem through the Fuzzy Bee Colony Optimization

In the field of Swarm Intelligence, the Bee Colony Optimization (BCO) has proven to be capable of solving high-level combinatorial problems, like the Flight-Gate Assignment Problem (FGAP), with fast convergence performances. However, given that the FGAP can be often affected by uncertainty or approximation in data, in this paper we develop a new metaheuristic algorithm, based on the Fuzzy Bee Colony Optimization (FBCO), which integrates the concepts of BCO with a Fuzzy Inference System. The proposed method assigns, through the multicriteria analysis, airport gates to scheduled flights based on both passengers’ total walking distance and use of remote gates, to find an optimal flight-to-gate assignment for a given schedule. Comparison of the results with the schedules of real airports has allowed us to show the characteristics of the proposed concepts and, at the same time, it stressed the effectiveness of the proposed method.     

基于近似模型的车辆操纵稳定性及平顺性的优化研究

简述了基于近似模型的车辆操纵稳定性及平顺性的优化设计方法.利用多体动力学软件ADAMS/Car建立了某轿车整车多体动力学模型,并确定了车辆操纵稳定性及平顺性的评价目标.以悬架弹簧刚度、减振器阻尼特性和横向稳定杆刚度为设计变量,利用近似优化数学模型对该轿车进行了操纵稳定性和行驶平顺性的多目标优化计算.结果表明,近似模型技术对于汽车性能的平衡优化是一种十分有效的方法.     

铁路旅客旅行换乘方案优选算法

为给铁路旅客选择合理的旅行方案提供参考,以旅行目标值与换乘目标值之和最小作为目标函数值,考虑旅客从起点站出发、最终到达终到站、在中转站进出平衡的约束条件,建立旅客旅行换乘方案选择问题的数学模型。分别给出旅行时间、换乘次数、票价、距离、到发时刻和综合指数6种目标权值的确定方法,提出最短路法和列车匹配法2种求解方法。最短路法是通过构造并简化旅客运输网络,求出网络上若干条次短路,再根据各条次短路上列车的接续,构造列车换乘方案网络图,根据该网络的目标权值确定最短路,得到最优换乘方案。列车匹配法是根据列车运行图信息直接搜索发、到站的接续列车集合,求其两列车对应的重合停车站,根据重合停车站集合的情况选择迭代步数,剔除显然不利方案,构成换乘方案,根据方案的权值进行比选,得到最优换乘方案。对2种算法均用C#编程实现,并用现有的全路客票数据进行检算。计算结果表明:2种算法均能得到最优换乘方案;列车匹配法所用计算时间比最短路法少160 ms。     

基于遗传算法的高速铁路行车调整模型

高速铁路采用“高中速列车共线运行”的运输模式,其行车调度具有高实时性和整体性两大特点。以列车计划运行图为优化目标,给出运行图之间的距离定义,建立列车运行调整数学模型,给出列车的发车时刻、股道数量、列车在区间的运行时分、追踪运行间隔时间、维修天窗时间5个约束条件表达式。按照遗传算法的原理,采用罚函数的方法对数学模型中的约束条件进行处理并建立适应度函数,采用整数编码方法对个体进行编码,并定义交叉算子和变异算子。基于遗传算法的调整算法流程开发列车运行调度仿真子系统。仿真结果表明:使用该模型可大大减轻调度人员的工作量,彻底摒弃了在计算机上手工拖动运行线确定列车运行时刻的调整方式,提高了列车运行调整的科学性。该模型已应用在高速铁路综合调度仿真系统中。     

多车多件货物装载布局优化模型与算法

以多车多件货物装载布局方案为研究对象,建立以标记载重量和有效容积综合利用率最大为目标函数,以货物合重心不超过容许偏移量、各件货物摆放位置不重合、货物不超出承载车辆边界、车辆承载货物总重量不超过车辆标记载重最,车辆承载货物总体积不超过车辆有效容积、货物不被重复装载等为主要约束条件的多车多件货物装载布局优化模型.设计以类First Fit划分算法和重容比为基础的模型求解算法,以制定货物装载布局方案.实例表明:用所提出的模型和算法能快速获得车辆利用效果良好、货物装载布局合理的装载布局方案.     

Identification of Dynamic Parameters Based on Pseudo-Parallel Ant Colony Optimization Algorithm

IntroductionReal ants are capable of finding the shortest pathfrom a food source to the nest. Inspired by this factand the behavior of ant colonies, a novel optimizationalgorithm called ant system (AS) was first developedby Dorigo in1992[1]. In the following years, diversemodifications of the AS algorithm were made andapplied to many different types of optimization prob-lems, and satisfactory results were obtained. Re-cently, the AS algorithm has been extended to an al-gorithm for solving d…     

基于作业成本法和目标成本法集成的船舶敏捷制造成本控制模型研究

通过对作业成本法和目标成本法集成和对船舶敏捷制造过程进行分析,提出了基于LCC的船舶敏捷制造作业成本和目标成本集成的控制方法,并建立了基于作业成本法和目标成本法集成的船舶敏捷制造成本控制模型,在工期-成本均衡的情况下实现船舶敏捷制造的成本最优。