地铁与市郊铁路过轨运营下列车开行方案研究

在分析地铁与市郊铁路过轨运营特点的基础上,以乘客节省的总旅行时间最大化和地铁运营企业增加的总费用最小化为目标函数,建立了过轨运营下列车开行方案双目标规划模型,并设计了基于模糊数学规划的求解算法.以某两条轨道交通线路为算例,研究过轨运营开行方案并对相关参数进行灵敏度分析.研究结果表明,地铁与市郊铁路过轨运营既可节省乘客总旅行时间又可增加运营企业收益,且过轨客流需求越大、过轨站换乘时间越长、过轨方缴纳的过轨费用越少、过轨列车运营组织方案越合理,过轨运营效果越显著.     

Workspace analysis to generate a collision-free torch path for a ship welding robot

We propose a method to determine the optimal initial location and to generate torch paths for a ship welding robot with 6 degrees of freedom (DOF). The optimal initial location is determined using an objective function, which is set up by combining constraints on the torch posture, manipulability, and the range of each joint angle to avoid collisions. A genetic algorithm (GA) is used to optimize the objective function because it does not require additional derivatives. After the initial location is determined, torch paths are generated by interpolating the starting point, endpoints and torch postures using inverse kinematics. Our method can be applied to automate the welding job for each block during ship building, irrespective of the shape of the robots, by changing the objective function.     

船体分段制造最低成本的二次规划模型及其求解

以分段建造费用与工时成线性关系为前提建立的船体分段制造最低成本数学模型其约束条件呈线性关系,目标函数边际收益递减,将最低成本模型改进为二次规划,利用EXCEL工具进行求解,实例计算逼近全局最优,方法简单实用.     

浙江省公路网车辆OD数据库管理系统开发研究

基于公路网OD调查数据现状管理与深度利用的需要,结合浙江省公路网车辆OD数据库管理系统的开发．对系统设计原则与开发平台、功能与框架、技术流程以及关键技术进行详细阐述,可为今后建立更科学和完善的数据库系统提供参考。     

城乡一体化的公交服务体系规划理论与实践研究

随着我国经济的不断发展,公共交通发挥着越来越重要的作用。城市化进程的加快和道路基础设施的改善为城乡一体化的公共交通体系提供了广阔的发展前景。研究了城乡一体化的公共交通服务体系规划的理论框架,并以汕头市为应用实例,提出了规划的可行性和实践性。     

组团式大城市客运综合换乘枢纽布局规划方法

为了使客运综合换乘枢纽布局适应中国大城市用地布局特征,分析了枢纽布局与城市土地利用、客运需求走廊分布和交通网络的关系,提出了宏观布局、微观选址的枢纽布局规划方法。宏观布局以公交导线土地开发为理念,确定枢纽的选址区域;微观选址以提高居民出行效率为目标,以用地性质、平均容积率及与客运需求走廊的距离为约束,建立非线性选址规划模型,确定枢纽的最佳位置。应用结果表明:应用该方法确定的枢纽选址区域与多中心组团式城市用地布局规划相一致,枢纽选址确定的最佳位置,其500m半径范围内覆盖的人口和就业岗位最高,而且能有效地反映枢纽布局与城市土地利用的互动性。     

物流中心选址与规模的层次优化模型

同时考虑生产商和分销商的利益,采用双层规划模型来描述物流中心选择以及规模问题.上层规划从生产商的角度出发,通过调整物流中心位置及规模使生产商的生产成本、运输成本和经营成本最小；下层规划从分销商的角度出发,通过调整从各个物流中心进货的数量使自身的平均运输成本最低.设计了基于遗传算法的求解方法,并用数值算例验证了模型和算法的有效性.     

Improving maritime inventory routing: application to a Brazilian petroleum case

The crude oil offloading and supply problem (COSP) is a type of operation maritime inventory routing (MIR) problem encountered by petroleum companies. In COSP, the company not only is responsible for the ship scheduling to carry the crude oil from production sites to discharge ports but also must maintain inventory levels at both ports (production and consumption) between safety operational bounds to avoid disruptions in its crude oil production and/or refining processes. We show how to improve significantly the decision-making process in a Brazilian petroleum company using a mixed-integer linear programming (MILP) model to represent COSP. Comparison tests with a current ship-scheduling method adopted in the company indicated that the use of the MILP model increased the transportation efficiency and reduced costs by 20% on average. In addition to the quantitative gains, the use of a MILP model to solve COSP has succeeded when encountering real-life events, such as variation in production or consumption rates, berth unavailability, and changes in the storage capacities at ports.     

Multi-objective optimization of train routing problem combined with train scheduling on a high-speed railway network

Based on train scheduling, this paper puts forward a multi-objective optimization model for train routing on high-speed railway network, which can offer an important reference for train plan to provide a better service. The model does not only consider the average travel time of trains, but also take the energy consumption and the user satisfaction into account. Based on this model, an improved GA is designed to solve the train routing problem. The simulation results demonstrate that the accurate algorithm is suitable for a small-scale network, while the improved genetic algorithm based on train control (GATC) applies to a large-scale network. Finally, a sensitivity analysis of the parameters is performed to obtain the ideal parameters; a perturbation analysis shows that the proposed method can quickly handle the train disturbance.     

TRIP DISTRIBUTION MODELLING USING FUZZY LOGIC AND A GENETIC ALGORITHM

This article examines possibilities for the application of soft computing techniques for the prediction of travel demand. The model, based on fuzzy logic and a genetic algorithm, successfully solves the trip distribution problem. The possibilities of using the proposed model in solving trip generation, modal split and route choice problems have also been indicated. The model has been tested on a real numerical example. Exceptionally good correspondences between estimated and real values of passenger flows have been obtained.