考虑退货不确定性的多层次多站点逆向物流网络选址优化研究

在退货量不确定情况下,为追求电商企业逆向物流网络成本最小化,建立了多层次多站点的混合整数规划模型。将目标区域进行网格化处理,通过球上距离公式计算相邻备选站点、不同层次备选点间的运输距离,使用蒙特卡罗法模拟退货量,并设计了双染色体编码的遗传算法进行求解。算例验证了模型算法的可行性,并且得出了逆向物流网络成本最小时,快递站点和退货处理中心的选址,快递站点的选址与退货量大小存在对应关系,研究客户退货量会使物流网络选址得到优化。     

基于K-means聚类算法与重心法的故障共享单车回收中心选址优化

共享单车已日渐成为人们短途出行的重要交通工具，但共享单车市场一贯采用“重投放，轻维护”的发展模式，而共享单车使用中的正常损耗及人为破坏等造成的故障车数量却十分庞大，对其回收修复或报废的任务繁重，这也成了共享单车市场逆向物流亟待解决的难题。该文立足武汉共享单车市场，通过对故障共享单车报废点的聚类分析，基于运输成本导向，使用重心法探寻回收中心最佳选址点，以解决故障共享单车回收成本和效率问题。对模型的模拟验证表明，优化后的回收中心选址点不仅能降低故障共享单车回收成本，而且相比武汉市现有的三个分布较远的回收中心，其总体运营成本更低，故障共享单车回收效率更高，便于共享单车的分区域运营管理。事实证明，基于K-means聚类算法与重心法确定回收中心选址问题不仅操作简单，可行性高，而且方便快捷，相较于现实中单一考虑成本等的选址方式，此模型更能兼顾多方面因素，优势明显。基于K-means聚类算法与重心法来确定回收中心选址，适用于城市的各个区域，选点精确又方便高效，模型具有较强的实用性。     

警车配置及巡逻方案研究

以警车的配置与巡逻方案为研究对象,建立了一套警车巡逻模型,并提出巡逻效果显著度及隐藏性的评价标准,分别针对警车初始位置配置与巡逻方案的制定,提出警车配置优化选址的贪婪算法与基于多Agent的警车巡逻方案设计方法,给出了不同情景下的配置及巡逻方案:①在只考虑警车选址配置的情况下,配置19辆警车可以使全市路网警车覆盖率达到92.8%;②在顾及巡逻效果显著性与隐藏性的情况下,配置25辆警车使全市路网在整个巡逻过程中平均警车覆盖率达到90.9%;③在配置10辆警车的情况下,使得全市路网在整个巡逻过程中平均警车覆盖率达到61.5%.     

需求势能理论的配送中心选址方法的研究

物流配送中心选址的合理性直接影响着物流分销网络规划和优化.提出了针对物流网点选址的需求势能理论,并提出了一种基于需求势能的分销物流系统中配送中心的选址实现方法.最后通过实例证明,该方法简便快捷,结果正确合理,为解决此类配送中心选址问题提供了科学的指导依据.     

化工园区应急设施区间规划选址模型研究

应急设施选址受应急物资需求量的影响。为优化应急设施选址布局,提高突发事件应急处置能力,以化工园区突发事件为研究背景,对化工园区突发事故下应急设施选址进行研究。考虑到化工园区突发事件的随机性和复杂性、突发事件应急物资需求的不确定性等特点,以应急设施选址安全性最大、经济性和服务效益最好为目标,基于传统确定性应急设施选址模型,构建了不确定需求条件下化工园区应急设施选址区间规划数学模型。模型中应急物资需求量是一个区间值,通过引入区间规划理论和模糊理论对模型进行求解,不仅避免了不确定参数随机概率分布的波动率,而且也降低了模型求解过程中的不确定性。最后,以园区各企业潜在事故为工程背景进行实例分析,得到园区应急设施的布局方案。结果表明,模型的求解效果较好,可为园区应急设施选址决策提供参考依据。     

基于综合效益的城市地下物流网络设计与优化方法

针对城市地下物流系统(Underground Logistics System,ULS)的特征,对一系列ULS网络节点选址与优化问题进行了建模分析.1)从解决城市交通拥堵的角度出发,探讨了物流地上地下分配的三种方案,并建立了地下货运OD评价模型.2)综合权衡货运量与货源距离,基于改进的模糊C均值聚类确定ULS—级节点的选址和辐射范围.3)对每个一级区域构建了ULS二级节点选址优化模型,通过人工免疫算法搜索最少覆盖节点群及节点的最优归属.4)建立多目标ULS网络规划模型,结合Prim算法与Dijkstra算法实现货物地下运输路径的最优选择,并采用栅格覆盖的思路在节点服务范围内对ULS网络进行费用优化.5)提出ULS网络效能评估指标,设置中心节点以提高系统运输效率和抗风险能力.     

双层级医疗设施选址问题及禁忌搜索算法

分级诊疗有利于充分利用已有的医疗资源,是医疗卫生体制改革的重要内容,因而在医疗设施选址时需要考虑医疗机构的层级性。本文以两个层级的医疗设施作为选址研究对象,建立了双层级多样流的混合整数规划模型。针对该模型的特点,设计了一种基于禁忌搜索的算法确定最优选址策略。最后,以上海市某区社区卫生服务中心以及区域医疗中心为研究对象,给出相应两个层级医疗设施的选址方案,并对相关参数对选址结果的影响进行了分析。算法求解结果为有就医需求的居民提供指派,使该区域的医疗资源利用率得到了提高,医疗设施配置也更加合理均衡。     

线状需求下的长江航道危险品应急中心选址优化

本文分析了长江航道危险品船舶对应急中心救援服务的线状需求特征,基于点状需求的设施选址模型,构建了全覆盖下的最小成本选址模型,实现了线状需求特性与最小成本的最优结合。将点状需求的设施选址研究延伸到线状需求的设施选址研究领域。并且针对模型设计了确定性规划算法和遗传算法。最后以长江航道为具体算例,对比了确定性规划算法和遗传算法对模型进行求解的效率及精度。实例表明,本文建立的基于线状需求的应急中心选址模型是符合实际的,确定性规划算法相对于遗传算法可以在更短时间内求得较稳定的最优解;遗传算法运行时间相对较长,且结果稳定性较差。     

零售业连锁网点选址与布局演化模型

蚁群算法是近年来出现的一种新型仿生优化算法,是求解复杂优化问题有效方法.本文建立了基于蚁群算法的零售业连锁网点选址与布局演化模型,并利用Matlab进行仿真研究.通过对模拟结果的分析,验证了零售业连锁网点的选址与布局规律.     

基于两阶段启发式算法的物流配送选址-路径问题研究

为了解决配送中心选址与带时间窗的多中心车辆路径优化组合决策问题,利用双层规划法建立了配送中心选址与车辆路径安排的多目标整数规划模型,针对该模型的特点,采用两阶段启发式算法进行了求解。首先,通过基于聚集度的启发式算法对客户进行分类,确定了备选配送中心的服务范围;然后,基于双层规划法,以配送中心选址成本最小作为上层规划目标,以车辆配送成本最小作为下层规划目标,建立了多目标整数规划模型;最后,利用改进的蚁群算法进行了求解。通过分析实例数据和Barreto Benchmark算例的实验结果,验证了该模型的有效性和可行性。     

Applying min–max <Emphasis Type="Italic">k</Emphasis> postmen problems to the routing of security guards

The most essential and alluring characteristic of a security estate is the estate's ability to provide 24-h security to its residents, of which the continual patrolling of roads and paths is vital. The objective of this paper is to address the lack of sufficient patrol route design procedures by presenting a tabu search algorithm capable of generating multiple patrol routes for an estate's security guards. The paper shows that the problem of designing these routes can be modelled as an Arc Routing Problem, specifically as min–max k postmen problems. The algorithm is illustrated with a real problem instance from an estate in Gauteng, South Africa. The patrol routes generated by the algorithm provide a significant improvement in the even patrolling of the road network, and a more balanced work distribution among guards. The algorithm is also tested on several benchmark problems from literature.     

Bi-criteria dynamic location-routing problem for patrol coverage

In this paper, we address the problem of dynamic patrol routing for state troopers for effective coverage of highways. Specifically, a number of state troopers start their routes at temporary stations (TS), patrol critical locations with high crash frequencies, and end their shifts at other (or the same) TS so the starting points for the next period are also optimized. We determine the number of state troopers, their assigned routes, and the locations of the TS where they start and end their routes. The TS are selected from a given set of potential locations. The problem, therefore, is a multi-period dynamic location-routing problem in the context of public service. Our objective is to maximize the critical location coverage benefit while minimizing the costs of TS selections, vehicle utilizations, and routing/travel. The multi-objective nature of the problem is handled using an ?-constraint approach. We formulate the problem as a mixed integer linear programming model and solve it using both off-the-shelf optimization software and a custom-built, efficient heuristic algorithm. The heuristic, utilizing the hierarchical structure of the problem, is built on the decomposition of location and routing problems. By allowing routing to start from multiple locations, our model improves the coverage by as much as 12% compared with the single-depot coverage model.     

110警车配置及巡逻方案

针对110警车调度问题,引入了图论中的最短路算法以及计算几何的相关理论,建立了车辆调配模型、巡逻路线模型以及基于模糊数学的评价指标模型.另外,用C++编写了一个可视化的软件,不仅实现了手动描点,自动求出覆盖线段集合的功能,同时利用计算机模拟警车的巡逻路线,最后通过计算机检验得到结果,其合理性和实用性都令人满意.针对问题一,通过人机结合,配置17辆警车就能实现D1的目标,很好地兼顾了警车巡逻的运行成本,减少公安部门车辆和人员等的投入.针对问题二,采用模糊数学相关理论使评价指标实现了从定性到定量的转变.针对问题三和六,在D1的基础上,兼顾了巡逻效果的显著性,采用最少被巡逻道路优先的贪心算法建立了动态巡逻模型,得到了合理的巡逻方案.在此方案中,我们动用了30辆警车完成了问题一的目标.另外还额外考虑了案发事件概率不均匀分布的情况,建立了改进模型.针对问题四,在完成问题三指标的基础上,为了尽可能提高巡逻车辆的隐蔽性和增强巡逻效果,采用轮盘赌算法来引入随机性.针对问题五,采用最远距离道路优先贪心策略,使模型尽可能满足条件D1,D2.针对问题七,提出了一些额外因素及其解决方案,进一步完善了模型,使模型更贴近现实.     

Infrastructure security games

Infrastructure security against possible attacks involves making decisions under uncertainty. This paper presents game theoretic models of the interaction between an adversary and a first responder in order to study the problem of security within a transportation infrastructure. The risk measure used is based on the consequence of an attack in terms of the number of people affected or the occupancy level of a critical infrastructure, e.g. stations, trains, subway cars, escalators, bridges, etc. The objective of the adversary is to inflict the maximum damage to a transportation network by selecting a set of nodes to attack, while the first responder (emergency management center) allocates resources (emergency personnel or personnel-hours) to the sites of interest in an attempt to find the hidden adversary. This paper considers both static and dynamic, in which the first responder is mobile, games. The unique equilibrium strategy pair is given in closed form for the simple static game. For the dynamic game, the equilibrium for the first responder becomes the best patrol policy within the infrastructure. This model uses partially observable Markov decision processes (POMDPs) in which the payoff functions depend on an exogenous people flow, and thus, are time varying. A numerical example illustrating the algorithm is presented to evaluate an equilibrium strategy pair.     

Contributions to a Theory of Patrol Scheduling

The problem considered in this paper is that of scheduling police patrols in a random pattern. This involves generating patrol routes as well as schedules for dispatching patrol vehicles. A solution to this problem is obtained by specifying minimum average patrol requirements on each route segment in a network and then developing a procedure which meets these requirements while minimizing the total patrol effort. Introducing vehicles into the network in a Poisson stream results in Poisson streams in each route segment and so ensures that an observer cannot use previous history for predicting arrival patterns. This solution also has the property that the number of patrol cars in the network is a Poisson random variable for which the steady-state can be achieved immediately. The steady-state distribution function is also used to determine the number of patrol cars required.     

基于点截集的围堵嫌犯模型

研究了在突发事件中交巡警对在逃嫌犯的围堵问题, 该问题为2011年全国大学生数学建模竞赛B题的一部分。接到报警后,交巡警服务平台的警力需要指派到路网路口以堵截嫌犯。将该问题转化为阻止嫌犯逃到特定点集的问题;并分析了怎样判断被选为围堵点的点集对一个指定点形成包围的问题。推广了点截集的概念,给出了判断点集是否为点截集和紧点截集的优化模型。然后将判断是否为点截集的模型转换为约束集合, 用于建立围堵嫌犯模型,以四个不同的优化标准分别建立了围堵问题的0-1整数规划模型。并给出了部分模型的Lingo算例。     

基于最大最小蚂蚁系统的物流配送中心选址算法的研究

提出了一种基于信息素自适应调节的最大最小蚂蚁系统的多物流配送中心选址算法,利用改进的蚁群算法的路径寻优机制结合蚂蚁聚集尸体的行为模式,根据物流配送总成本最低的原则将各配送点与候选配送中心进行聚类,合理选择配送中心。将已有物流配送模型进行拓展,加入经营管理成本。分别利用基本蚁群聚类算法和改进的蚁群聚类算法对配送中心选址进行仿真,实验结果表明在解决大规模配送中心选址问题时,改进的算法在解的质量和收敛速度方面明显优于基本蚁群聚类算法。     

Beat patrolling in urban areas A case study

Urban police patrol work has been analysed in the present paper. Working on the crime-rate, as reported by the police department, a plan has been worked out to ensure an effective police patrol in a given locality. This locality is predominantly a “business/marketing area”. Many problems connected with beat patrol like type of beat, route numbers, beat-ranking and others have been discussed. The analysis will help the police station to understand the beat patrol problem. Alternative beat routes have been suggested, together with deployment. Beat ranking may help in assessing the vulnerability of an area and as such proper steps may be taken in advance to prevent the occurrence of the crime. It is expected that patrolling will be more effective and useful after the implementation of this study.