不确定箱重下内河集装箱班轮航线配载决策

与集装箱海运相比内河集装箱班轮运输具有其独特性,同时对于内贸箱而言,货主订舱时箱重信息的不确定性导致其航线配载决策变得更加复杂.本文考虑不确定箱重影响,以最小化航线班轮堆栈占用数量为目标,构建内河集装箱班轮航线配载决策的随机规划模型.为实现求解,基于随机规划理论,采用机会约束描述随机约束,将随机规划模型转化为随机机会约束规划模型,并设计混合邻域搜索算法求解.算法由蒙特卡罗随机模拟、神经元网络训练及邻域搜索启发式3个部分组成.算例研究表明,混合邻域搜索算法的鲁棒性较好,可实现配载计划对不确定因素的有效吸收.     

城市轨道交通快慢车开行方案双层规划模型

针对城市轨道交通客流时空分布不均衡特征和乘客长距离出行时效需求,并考虑乘客的换乘行为,提出基于双层规划模型的快慢车开行方案优化方法.上层模型以乘客出行时间和列车周转时间最小为目标,考虑快慢车开行比例、线路通过能力等主要约束,构建多交路条件下的快慢车开行方案优化模型;下层模型通过设计换乘网络刻画乘客换乘行为,构建快慢车方案下的客流分配模型.设计粒子群算法求解所建双层规划模型,以广州地铁14号线为案例,验证本文构建模型的有效性和适用性.     

突发环境下城市道路网关键路段集识别

为了更好地判断出突发环境下城市道路网络中的关键路段,本文结合路网脆弱性分析方法,构建了一种涵盖单条到多条路段失效的关键路段集识别模型.首先,对路网进行随机攻击,运用网络效率、最大连通子图等鲁棒性指标寻找潜在关键路段;然后,引入0-1变量,建立一个含道路通行能力约束的非线性优化模型;再以此为基础,用分段线性化手段处理目标函数与约束条件,将模型转化为一个混合0-1规划问题;最后,以分支定界法求解模型并设计算例验证.结果表明：突发环境下的路网关键路段集一般不是若干关键路段的简单集成,其构成元素在几何拓扑层面上也不具有邻接关系;而且随着失效路段数的增多,路网鲁棒性与总阻抗变化量之间会呈现出较显著的负相关关系,可用“逆向”曲线进行刻画,效果良好.     

连续流交叉口左转非机动车优化设计方法

为了提升连续流交叉口的通行能力,消除其主信号处左转非机动车与直行机动车的冲突,提出了一种左转非机动车优化设计方法.优化模型以机动车通过量最大为优化目标,考虑了信号相位相序、周期时长、绿灯时长等约束条件,建立线性规划优化模型.通过案例和敏感性分析,验证了该设计方法的优化效益.研究结果表明,该方法不仅能在高流量情况下显著提升交叉口通行能力,使得原本处于过饱和状态的交叉口变为不饱和,而且在高流量或低流量情况下,都有助于减少交叉口延误.进一步发现,左转非机动车流量每增加100辆/h或直行机动车流量比例每增加1.5%(直行机动车流量比例大于40%),优化设计对机动车最大通过量的提升比例增加4.5%.     

不使用实时操作系统实现任务定时切换

介绍电动汽车ECU程序设计新方法,实现不使用实时操作系统,同时又能够将操作模块化、任务化,并将各个任务间的耦合降至最低.     

基于双层规划的竞争性选址问题研究

以往对竞争性选址问题的研究,都是从服务提供者的角度考虑问题,寻求市场份额最大化或成本最小化的选址方案.实际中,竞争性选址方案的确定应该是服务提供者与服务需求者上下两层关系互动的过程,并且仅仅考虑市场份额最大化或成本最小化是不够的,企业往往更关心的是利润.针对寡头垄断市场配送中心的选址问题,建立基于双层规划的竞争性选址模型,考虑属于不同企业的配送中心对于配送服务需求者的竞争问题,上层目标函数追求配送中心的利润最大化,下层目标函数是配送服务需求者的广义费用最小.给出了遗传算法求解规模较大的问题,通过一个算例验证模型和算法的可行性.     

Multi-objective bilevel construction material transportation scheduling in large-scale construction projects under a fuzzy random environment

Abstract

This paper investigates a transportation scheduling problem in large-scale construction projects under a fuzzy random environment. The problem is formulated as a fuzzy, random multi-objective bilevel optimization model where the construction company decides the transportation quantities from every source to every destination according to the criterion of minimizing total transportation cost and transportation time on the upper level, while the transportation agencies choose their transportation routes such that the total travel cost is minimized on the lower level. Specifically, we model both travel time and travel cost as triangular fuzzy random variables. Then the multi-objective bilevel adaptive particle swarm optimization algorithm is proposed to solve the model. Finally, a case study of transportation scheduling for the Shuibuya Hydropower Project in China is used as a real world example to demonstrate the practicality and efficiency of the optimization model and algorithm.     

Synchronized Production and Transportation Planning Using Subcontracted Vehicles in a Production-Distribution Network

Abstract

Effective management of interfaces between procurement, supply, production and distribution for higher efficiency in the supply chain is an important issue in global manufacturing, where the synchronization of production and transportation planning represents important savings in operational costs. This paper focuses on the synchronization of production planning and transportation planning in a production distribution network, where transportation is subcontracted to a professional transportation enterprise (PTE) for vehicle-hiring. Dynamic and flexible numbers of vehicles are used to cater for fast changing market demands. Thus, the number of vehicles to be hired is viewed from the planning point of view as an operational decision considered simultaneously with production and transportation planning. A mathematical model – SPTP/MTDS – for synchronized production and transportation planning under multiple times and direct shipping strategy (MTDS) is discussed, and a Lagrange relaxation decomposition-based two layer decision procedure (LRD-TLDP) is developed. By introducing artificial decision variables and Lagrange multipliers, SPTP/MTDS is decomposed into a production decision sub-problem (SPTP-PD), and a distribution decision sub-problem (SPTP-DD). A priority-based assignment heuristic and a partial chain-based genetic algorithm are developed to solve SPTP-PD and SPTP-DD, respectively. An illustration of the application of the model in an electronic appliance manufacturing enterprise in China is presented.     

Optimal tank-trailer routing using the ILOG constraint programming – a Taiwan case study

Abstract

This paper investigates the routing of pressurized tank trailers and proposes a scheduling plan which ensures the practical delivery of industrial gases under the objective of reducing transportation costs. Using constraint programming, we solve a combinatorial optimization problem that incorporates both hard and soft constraints for routing and scheduling tank trailers. Hard constraints are resource and safety/regulation constraints, whereas soft constraints are utilization and efficiency constraints. This approach enables tank-trailer routing and scheduling management to consider different combinations of parameters and view the results in ‘real-time.’ The routing and scheduling results based on a case study in Taiwan fulfil the goals of avoiding risks associated with transporting industrial gases, and attaining efficient delivery while conforming to regulations and consistent with good business practice. The results also suggest that significant economies in distribution costs are possible.     

基于CAN Bootloader的电动汽车远程数据更新系统设计

基于飞思卡尔MC9S12X系列16位微控制器,阐述CAN Bootloader的原理和工作过程及应用,并实现远程数据更新功能。实验表明,将CAN Bootloader远程数据更新应用于汽车CAN总线中,实现远程下载或远程标定,使CAN节点更具灵活性和可扩展性,同时提高产品开发的效率。