Optimal Configuration of Fault Location Measurement Points in DC Distribution Networks Based on Improved Particle Swarm Optimization Algorithm

The escalating deployment of distributed power sources and random loads in DC distribution networks hasamplified the potential consequences of faults if left uncontrolled. To expedite the process of achieving an optimalconfiguration of measurement points, this paper presents an optimal configuration scheme for fault locationmeasurement points in DC distribution networks based on an improved particle swarm optimization algorithm.Initially, a measurement point distribution optimization model is formulated, leveraging compressive sensing.The model aims to achieve the minimum number of measurement points while attaining the best compressivesensing reconstruction effect. It incorporates constraints from the compressive sensing algorithm and networkwide viewability. Subsequently, the traditional particle swarm algorithm is enhanced by utilizing the Haltonsequence for population initialization, generating uniformly distributed individuals. This enhancement reducesindividual search blindness and overlap probability, thereby promoting population diversity. Furthermore, anadaptive t-distribution perturbation strategy is introduced during the particle update process to enhance the globalsearch capability and search speed. The established model for the optimal configuration of measurement points issolved, and the results demonstrate the efficacy and practicality of the proposed method. The optimal configurationreduces the number of measurement points, enhances localization accuracy, and improves the convergence speedof the algorithm. These findings validate the effectiveness and utility of the proposed approach.

Resource Allocation for Physical Layer Security in Heterogeneous Network with Hidden Eavesdropper

The tremendous performance gain of heterogeneous networks(Het Nets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for Het Nets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker(KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.

Location-Allocation in the Two Conditions of Candidate and Non-Candidate Places with Fuzzy Relations between Facilities Using Euclidean Square Method

Nowadays, identification, ranking criteria and location of services are important in the planning and designing of city. In fact, it helps the authorities and managers make better decisions in selecting the best locations to establish urban service centers. The issue of access to urban services is kind of important issue that affects various dimensions of the city. Laboratory service is an example of this kind that the necessity of access to them is crucial for everyone. Decision making to locate the lab is not only necessary in terms of services and costs to users but also, it is essential in the development of city and the spatial distribution pattern of demand. In this paper, the goal was to determine laboratories location using Euclidean square and fuzzy logic, by two different methods to examine and desirable locations for future planning. Also, selected locations for laboratories are significant considering the improvement of service and reducing the cost and time of access to public.

Integration of Location-Allocation and Accessibility Models in GIS to Improve Urban Planning for Health Services in Al-Madinah Al-Munawwarah, Saudi Arabia

In this study, accessibility and location-allocation models have been integrated into GIS to improve spatial planning and environmental sustainability of health services in Al-Madinah Al-Munawwarah. This integration provides a planning framework in order to check the efficiency of the spatial allocation of health services and to generate alternatives either by proposing an active service or to improve an existing one. To achieve these objectives, the accessibility to the service area was analyzed within the analysis of health services networks, which are divided into eight types: public hospitals, specialized hospitals, health units, healthcare centers, infirmaries, clinic complexes, the Red Crescent Center, and ambulance facilities, with time intervals of (5 minutes - 10 minutes - 15 minutes) to access coverage ranges, and the location-allocation model was used based on the maximum coverage model within a response time not exceeding 15 minutes, The results of the study revealed the poor distribution of health services Al-Madinah Al-Munawwarah suffers from weak accessibility to health services coverage areas and is unable to meet the needs of its population at present. The current need for health services reached twenty-four locations, including two public hospitals, three specialized hospitals, two health centers, three ambulance facilities, four infirmaries, three clinic complexes, four health units, and three Red Crescent centers.

Application of the p-Median Problem in School Allocation

This paper focus on solving the problem of optimizing students’ orientation. After four years spent in secondary school, pupils take exams and are assigned to the high school. The main difficulty of Education Department Inspection (EDI) of Dakar lies in the allocation of pupils in the suburbs. In this paper we propose an allocation model using the p-median problem. The model takes into account the distance of the standards imposed by international organizations between pupil’s home and school. The p-median problem is a location-allocation problem that takes into account the average (total) distance between demand points (pupil’s home) and facility (pupil’s school). The p-median problem is used to determine the best location to place a limited number of schools. The model has been enhanced and applied to a wide range of school location problems in suburbs. After collecting necessary numerical data to each EDI, a formulation is presented and computational results are carried out.

Review of Methods to Calculate Congestion Cost Allocation in Deregulated Electricity Market

With maturing deregulated environment for electricity market, cost of transmission congestion becomes a major issue for power system operation. Uniform Marginal Price and Locational Marginal Price (LMP) are the two practical pricing schemes on energy pricing and congestion cost allocation, which are based on different mechanisms. In this paper, these two pricing schemes are introduced in detail respectively. Also, the modified IEEE-14-bus system is used as a test system to calculate the allocated congestion cost by using these two pricing schemes.

Experiment Design for the Location-Allocation Problem

The allocation of facilities and customers is a key problem in the design of supply chains of companies. In this paper, this issue is approached by partitioning the territory in areas where the distribution points are allocated. The demand is modelled through a set of continuous functions based on the population density of the geographic units of the territory. Because the partitioning problem is NP hard, it is necessary to use heuristic methods to obtain reliable solutions in terms of quality and response time. The Neighborhood Variable Search and Simulated Annealing heuristics have been selected for the study because of their proven efficiency in difficult combinatorial optimization problems. The execution time is the variable chosen for a factorial experimental design to determine the best-performing heuristics in the problem. In order to compare the quality of the solutions in the territorial partition, we have chosen the execution time as the common parameter to compare the two heuristics. At this point, we have developed a factorial statistical experimental design to select the best heuristic approaches to this problem. Thus, we generate a territorial partition with the best performing heuristics for this problem and proceed to the application of the location-allocation model, where the demand is modelled by a set of continuous functions based on the population density of the geographical units of the territory.

Geographical Analysis of Smoking in Leeds: A GIS-Based Location-Allocation Technique for the Optimal Location of Smoking Cessation Services

Smoking is associated with several illnesses in the UK. Smoking rate in Leeds is higher than the national average. Finding optimal locations for stop-smoking services will be a good place to start in reducing smoking rates. The study utilizes a GIS-Based location-allocation method for the optimal distribution of smoking cessation centres in relation to the spatial distribution of the smoking population in Leeds. The demand for the smoking cessation clinics was estimated based on the 2009 General Life Style (GLS) statistics on age and social class stratification of smoking rates for the UK. Leeds specific rates were then obtained from the 2001 census key statistics data on socioeconomic status and age structure for output areas via Census Area Statistics Website (CASWEB). The research findings show that spatial inequalities in smoking rate exist in output areas of Leeds. Poorer and non-skilled populations are demonstrated to have higher smoking rates compared with wealthier neighbourhoods. The study confirms the capability of GIS-Based location-allocation techniques to be useful modelling tools for determining the best locations for health facilities. The model allocates services in relation to the spatial patterns of demand in a fashion that minimises average travel distance.

The Impact of Residential and Non-Residential Demand on Location-Allocation Decision-Making: A Case Study of Modelling Suitable Locations for EMS in Leicester and Leicestershire, England UK

The research examines the impact of residential and non-residential demand on facility location planning by comparing results from two location models: travel-to-work (TTW) and Residential model. The TTW model considers short-term changes in the state of the population due to travel-to-work (non-residential demand). By contrast, the Residential model uses a static snap-shot of the population based on official census estimates (residential demand). Comparison of both models was based on a case study of Emergency Medical Services (EMS) location-allocation planning problem in Leicester and Leicestershire, England, UK. Results showed that the using a static residential demand surface to plan EMS locations overestimates actual demand coverage, compared to a non-residential demand surface. Differences in location-allocation results between the models underscore the importance of accounting for temporal changes in the state of the population when planning locations for health service facilities. The findings of the study have implications for siting of EMS, designing, and planning of EMS service catchments and allocation of prospective demand to EMS sites. The study concludes that consideration of temporal changes in the state of the population is important for reliable and efficient location-allocation planning.

The Capacitated Location-Allocation Problem in the Presence of <i>k</i>Connections

We consider a capacitated location-allocation problem in the presence of k connections on the horizontal line barrier. The objective is to locate a set of new facilities among a set of existing facilities and to allocate an optimal number of existing facilities to each new facility in order to satisfy their demands such that the summation of the weighted rectilinear barrier distances from new facilities to existing facilities is minimized. The proposed problem is designed as a mixed-integer nonlinear programming model. To show the efficiency of the model, a numerical example is provided. It is worth noting that the global optimal solution is obtained.

A Differential Privacy Budget Allocation Method Combining Privacy Security Level

Trajectory privacy protection schemes based on suppression strategies rarely take geospatial constraints into account,which is made more likely for an attacker to determine the user’s true sensitive location and trajectory.To solve this problem,this paper presents a privacy budget allocation method based on privacy security level(PSL).Firstly,in a custom map,the idea of P-series is contributed to allocate a given total privacy budget reasonably to the initially sensitive locations.Then,the size of privacy security level for sensitive locations is dynamically adjusted by comparing it with the customized initial level threshold parameterµ.Finally,the privacy budget of the initial sensitive location is allocated to its neighbors based on the relationship between distance and degree between nodes.By comparing the PSL algorithm with the traditional allocation methods,the results show that it is more flexible to allocate a privacy budget without compromising location privacy under the same preset conditions.

多无人机辅助NOMA网络的联合无线资源分配算法

为了满足高容量需求和通信质量,提出了一种多无人机(Unmanned Aerial Vehicle, UAV)辅助下行非正交多址(Non-Orthogonal Multiple Access, NOMA)网络的联合定位、用户调度、用户配对和功率分配优化算法。在基站位置固定的网络场景下,推导出通用最优用户配对和功率分配策略闭式解。针对多小区场景,将无人机的位置优化问题转化为一个局部合作博弈问题,并证明所提博弈是一个精确的潜在博弈,它至少有一个纯策略纳什均衡(Pure Strategy Nash Equilibrium, PNE),且最优的纳什均衡(Nash Equilibrium, NE)能够最大化网络和速率。设计了一种集中分布式学习算法寻找最优PNE。仿真结果表明,该算法优于现有方案,显著提高了网络效用。

基于GIS的城市应急避难场所空间区划——以成都市主城区为例

为提升灾后城市整体应急避难服务能力,在综合考虑人口分布、交通网络、服务容量、建设成本和路网可达性等多因素的基础上,运用GIS空间分析技术,对四川省成都市主城区开展应急避难空间区划研究,提出高效、公平和经济的应急避难场所空间区划方案,形成1套科学的方案制定方法和流程。研究结果表明:成都市主城区可划分成10个应急避难分区,并确立14个最佳避难场所来满足区域内的应急避难需求;同时对实验外国语学校、丽都公园进行容量扩建,并升级浣花溪公园周边交通配套设施来优化应急避难场所空间区划,以此提升成都市主城区整体应急避难服务能力。研究结果可为城市人口转移避难安置工作规划和决策实施提供技术支持。

无人机群辅助边缘计算系统的任务卸载和资源分配联合优化

为提升无人机群辅助边缘计算系统在负载不均衡场景下的性能,构建了一种新的无人机群边缘计算系统,利用无人机之间卸载数据来提高计算资源的利用率,通过联合优化多架无人机的卸载方案、部署和资源分配,使得系统的时延和能耗加权和最小。该问题高度非凸,为此提出一种高效的双层优化算法——启发最优评价算法,上层使用粒子群算法优化无人机位置,下层在确定位置的情况下使用块坐标下降算法优化无人机的数据卸载和资源分配。仿真结果表明,所提方案可有效降低系统成本,与基准策略相比优势明显。

耦合优化蚁群算法与P-Median model的选址模型设计

为节省城建部门对于公共体育设施的投入成本以及提高城市人民生活质量,以运动场所优化选址为例,提出一种新型设施选址模型。该模型主要基于P-Median model(最小化阻抗模型)根据需求点数量从全部候选设施选址中选择设施空间位置,让用户达到离自己最近设施距离成本总和最小的目的,对选址的基本原则和实际情况提出要求,构造目标函数用于优化后蚁群算法求解进行选址工作。优化蚁群算法实现基于Python语言模块,通过改进蚁群原始信息素,提升原有算法的收敛速度,求出目标函数最优解,可以很好地模拟对于运动场所的选址。用二者耦合进行优势互补所设计的选址模型来搜寻研究区蚁群信息素浓度残留最大的栅格像元,从而确定未被已有设施点服务半径覆盖的最佳设施点建立位置。实验结果表明,该新型选址模型相较于最小化阻抗模型与最大化覆盖模型,新增优化设施点使整体服务半径覆盖率分别高出10.42%和6.95%,适合求解较为精确且小规模空间下的选址问题。

考虑患者转运的跨区域动态协同应急物流选址-分配优化研究

针对突发公共卫生事件下多个受灾地区之间跨区域应急资源配置的现实需求,研究考虑患者转运的跨区域动态协同应急物流选址−分配优化问题,构建跨区域的患者转运与应急资源协同配置两阶段优化决策模型。模型第1阶段优化确定患者动态变化与相应医院数量及其选址,第2阶段优化确定应急物资配送中心选址与应急物资分配。该优化模型同时考虑应急物流总成本(包括设施固定成本与运营成本)与转运时间2个优化目标,且考虑多周期动态变化的实际需求。针对上述优化模型特征,设计嵌入模型预测控制(MPC)方法的改进遗传算法。该算法将每个决策周期分为3个环节:1)疾病扩散预测环节,即每个周期开始时对疾病发展趋势进行预测;2)应急决策规划及实施环节,根据规划窗口的预测数据制定并实施应急选址−分配方案;3)数据更新与动态调整环节,即每个执行周期结束时,根据实际执行数据制定下一个周期决策。3个环节交互进行,相互迭代直到完成整个规划时期。最后,以贵州省跨区域的应急资源协同配置优化为例,验证所提优化模型及其求解算法的有效性。研究发现:与各区域独自应急相比,跨区域动态协同应急方案在转运时间没有明显增加的情况下,能有效降低应急成本,能够高效率地利用应急设施为感染患者提供救治。研究成果为突发公共卫生事件中多区域之间的协同应急资源配置优化提供决策支持。

基于最小权覆盖的医药电商配送中心选址及区域覆盖优化研究

配送中心选址及区域划分是物流配送过程中的关键环节,直接决定了配送时效及配送成本,在当今电子商务领域显得尤为重要。本文针对国内医药电商企业,提出了一种考虑药品配送时效的配送中心选址策略;随后建立该问题的整数规划模型,采用最小权顶点覆盖方法描述问题,并通过优先队列分支限界算法对此模型进行求解,得出最优选址结果;最后按最小运费原则将被重复覆盖区域进行再划分,得到配送中心选址及区域划分最终方案。本文基于上述策略为国内某头部医药电商企业提供了两种选址方案:保留企业原有配送中心并确定新配送中心选址点(改进选址方案)和从企业所有需求节点中重新为配送中心选址(重选址方案),并使用企业真实销量和物流数据进行算例分析。

中国西部地区全科医生资源配置公平性分析及需求预测研究

背景全科医生是居民健康的守门人,其资源的合理配置是实现卫生服务公平性的基本保障。目前我国对全科医生配置方面的研究主要集中于全国和部分单体省份,缺乏针对以西部地区为研究对象的全科医生人力资源配置的研究。目的评价2015—2020年我国西部地区全科医生资源配置现状,为西部地区优化全科医生资源配置提供参考。方法本研究数据来源于2016—2017年《中国卫生和计划生育统计年鉴》、2018—2022年《中国卫生健康统计年鉴》、2016—2022年《中国统计年鉴》。运用阿特金森指数和区位熵对西部地区全科医生配置进行总体测算和具体分解;运用灰色预测模型对西部地区2022—2025年全科医生需求量进行预测。结果2015—2020年西部地区全科医生数从39290人增加至94652人,年均增长率为19.23%;2015年和2020年按人口、经济和地理面积分布的阿特金森指数分别是0.1265和0.0493、0.1244和0.0382、0.7865和0.6944;2020年西部各省份的人口、经济、地理指标的区位熵分别在0.7943~1.2190、0.6970~1.3373、0.0432~7.7270,西南地区地理配置区位熵>1,西北地区人口配置区位熵优于地理配置,甘肃省、青海省和广西壮族自治区经济指标的区位熵在研究年限内均>1;灰色模型预测2022—2025年西部地区全科医生数量呈增长趋势。结论西部地区全科医生资源配置水平逐渐提升,结构逐步优化,但仍存在总量不足、分布不均、注册率较低、公平性较差等问题。建议应以地理分级为标准,以“调增优存”为原则,以职业吸引力为目标,以资源整合和区域协同为导向,进一步优化西部地区全科医生资源配置。

基于GIS网络分析的社区商圈布局研究

在浙江省“高质量发展建设共同富裕示范区”的战略背景下,结合“人本”生活圈的衍展概念,选取大数据采集、服务区需求、多因子叠加、位置分配运算模型等分析方法,归纳并探析临海市中心城区社区商圈发展特征及障碍,以优化社区商圈组织层次、空间布局、规模配置为抓手,从而达成对未来社区商圈规划标准和品质要求的共识。

无人机辅助边缘计算中安全通信与能效优化策略

无人机的灵活移动性在移动边缘计算系统中引起了广泛的关注。然而,空中窃听者的存在使它的安全传输仍然面对巨大的挑战。为了解决高安全通信速率与低能耗之间的矛盾,引入安全通信能效这一概念,即无人机安全通信传输速率与无人机能耗之间的比值。首先,在满足给定任务时延、无人机的CPU计算频率以及任务卸载率的约束下,提出一种最大化安全通信能效的卸载策略,即联合优化合法无人机悬停位置、CPU计算频率分配以及区分计算任务复杂度的卸载策略;同时从物理层安全角度提升了无人机-移动边缘计算场景下的安全通信。其次,由于该策略是一个复杂的非凸问题,将其解耦为3个子问题,通过块坐标下降法与连续凸逼近(SCA)相结合的全局优化算法来求解该非凸问题。仿真结果表明,针对不同任务复杂度的系统,所提策略都能在满足地面终端卸载需求的同时,平衡整体的通信安全性能和能耗之间的关系,并提高安全通信能效。