快递配送车辆路径优化研究

考虑到快递配送和物流配送的异同,在物流配送路径优化问题的基础上构建了符合快递配送路径优化问题的数学模型.设计了一种采用自然数编码,综合考虑快件数量、车辆载重、车辆容量等约束的解码方式的遗传算法.通过一个拥有20个配送点的快递配送案例,验证本文所构建模型和算法能够得到合理配送路径和各个配送点的服务时刻.最后通过灵敏度分析和四轮厢式货车算例验证表明:当前情况下,研究快递配送路径优化时,快件数量、快递员最长配送时间和各配送点的作业时间必须考虑;当前快递配送车辆的载重和容量满足当前需求,无需更换载重和容量更大的配送车辆.     

A framework to evaluate policy options for supporting electric vehicles in urban freight transport

Electric vehicles (EVs) are considered as a feasible alternative to traditional vehicles. Few studies have addressed the impacts of policies supporting EVs in urban freight transport. To cast light on this topic, we established a framework combining an optimization model with economic analysis to determine the optimal behavior of an individual delivery service provider company and social impacts (e.g., externalities and welfare) in response to policies designed to support EVs, such as purchase subsidy, limited access (zone fee) to congestion/low-emission zones with exemptions for EVs, and vehicle taxes with exemptions for EVs. Numerical experiments showed that the zone fee can increase the company’s total logistics costs but improve the social welfare. It greatly reduced the external cost inside the congestion/low-emission zone with a high population, dense pollution, and heavy traffic. The vehicle taxes and subsidy were found to have the same influence on the company and society, although they have different effects with low tax/subsidy rates because their different effects on vehicle routing plans. Finally, we performed a sensitivity analysis. Local factors at the company and city levels (e.g., types of vehicle and transport network) are also important to designing efficient policies for urban logistics that support EVs.     

Route design for last-in,first-out deliveries with backhauling

The retail route design problem extends the capacitated vehicle routing problem with time windows by introducing several operational constraints, including order loading and delivery restrictions (last-in, first-out), order-dependent vehicle capacity, material handling limits at the warehouse, backhauling, and driving time bounds. In this paper, the problem is modeled on a directed network for an application associated with a major grocery chain. Because the corresponding mixed-integer program proved too difficult to solve with commercial software for real instances, we developed a greedy randomized adaptive search procedure (GRASP) augmented with tabu search to provide solutions. Testing was done using data sets provided Kroger, the largest grocery chain in the US, and benchmarked against a previously developed column generation algorithm. The results showed that cost reductions of $4887 per day or 5.58% per day on average, compared to Kroger’s corresponding solutions.     

动态交通流诱导模型在交通出行服务中的应用研究

本文从浙江交通智能交通建设应用需求出发,分析了动态交通流诱导模型在浙江交通出行服务中的实际应用,提出了浙江交通高速公路、内河航道实时交通状况分析的方案。该方案包括了基于多个Agent诱导代理系统的诱导模型,交通流诱导系统框架等自主技术研究成果。同时,本文给出了在浙江交通出行服务实际应用中,结合GPS定位技术、GIS地理信息技术、GSM/CDMA无线通信技术,实现了浙江交通高速公路、内河航道实时交通状况的分析和播报的应用场景。     

A cooperative waiting strategy based on elliptical areas for the Dynamic Pickup and Delivery Problem with Time Windows

The purpose of this paper to present a cooperative scheduling algorithm for solving the Dynamic Pickup and Delivery Problem with Time Windows (DPDPTW). The idea behind cooperative waiting strategies is to calculate simultaneously the waiting times for all nodes in the solution. Classical non‐cooperative scheduling algorithms perform the scheduling for each route independently of the scheduling of the other routes. We present the Cooperative Scheduling Problem (CSP) based on the elliptical areas generated by vehicles waiting at their nodes. The CSP is solved by means of a genetic algorithm and is evaluated by using a set of benchmarks based on real‐life data found in the literature. Initially, two waiting strategies are presented: Wait‐Early‐Time scheduling and Balanced‐Departure scheduling. Extensive empirical simulations have been carried out by analyzing the degree of dynamism and the average waiting time, a new concept defined to take into account the gap between the time windows of pickup and delivery nodes. Copyright © 2016 John Wiley & Sons, Ltd.     

铁路信号集中监测系统中心网络

主要阐述了铁路信号集中监测系统中心网络的体系结构、动态路由协议和信号集中监测系统中心网络安全的重要性。     

城市轨道交通多交路运营线路通过能力损失及优化

多交路运营是城市网络化轨道交通系统常采用的运营组织方式之一。针对多交路运营的特点,利用运行图铺画的方法详细分析线路通过能力在单交路区段及双交路区段的损失值大小,并归纳出计算公式;进一步结合计算公式分析通过延长列车运行周期来提高通过能力的优化方法及其实施过程。最后指出该方法在实际应用中与车底运用数之间存在的矛盾,应根据线路特点在二者之间权衡利弊。     

城市轨道交通非高峰期列车交路方案优化

为降低轨道交通运营成本,同时保证乘客的服务水平,针对城市轨道交通非高峰期客流不均衡情况,对城市轨道交通非高峰期列车交路方案进行研究。考虑列车OD客流量、列车运行间隔、列车车底数及线路交路限制等特征,建立运营商成本最小化及乘客等待时间最小化的双目标多约束优化模型。其次设置不同的权重,利用遗传算法对模型进行求解。结果显示偏好程度不同,模型指定的优化方法不同。该模型能够灵活地设计非高峰期列车交路方案,这为城市轨道交通决策者提供决策支持,具有一定的指导意义。     

基于CO_2排放的车辆路径优化模型及其算法研究

物流不仅是能源消耗大户,同时也是CO2排放的重要来源。在分析配送车辆燃油消耗和CO2排放因素的多种车辆类型车辆路径问题特点的基础上,构建其相应的优化模型,并给出基于遗传算法的启发式求解算法。最后,针对该模型和求解算法进行数值算例仿真,研究结果显示:路径最短的路线不一定是能耗最小的路线;与传统基于路径最短的车辆路径对比,基于CO2排放的车辆路径总行驶里程较长,但其综合成本较低;遗传算法是解决绿色车辆路径问题的一个有效的求解算法。     

不确定环境下应急物资配送问题研究

针对受灾点的需求量、车辆从配送中心到受灾点的运行时间及单位成本为三角模糊数的应急物资配送问题,建立系统总费用最小和总的时间惩罚成本最小的双目标规划模型,利用模糊数的相关理论将模糊规划模型转化为确定型双目标混合整数规划模型,并由此设计了该模型的求解算法,通过算例说明了算法的可行性和有效性。分析表明,最优的车辆路径的决策方案与权重值ω关系密切,故决策者在决策时应根据实际情况选择合适的权重值ω。