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.

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.

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.

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.

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.

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.

Fast Convergence Resource Allocation in IEEE 802.16 OFDMA Systems with Minimum Rate Guarantee

Resource allocation in the context of OFDMA-based systems is challenging, given a combinatorial nature of the problem. In the context of IEEE 802.16 systems this problem is further exacerbated by additional constraints that are faced with its two dimensional frame nature. The main challenges associated with resource allocation in these systems are: mapping the allocated bandwidth resources to users in this two dimensional frame, power and frequency allocation, and Qo S guarantee. This optimization problem can usually be solved by an iterative algorithm. The solutions proposed have a constant step size in iterations which causes a long convergence time. For this reason, the solutions proposed are not applicable in IEEE 802.16 systems. In this paper we propose a novel resource allocation algorithm in IEEE 802.16 systems which has an adaptive step size in iterations while taking into account the minimum rate guarantee for users.

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 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.

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.

基于LA模型的潍坊市路外公共停车场选址研究

城市路外公共停车场建设已经成为城市基础设施建设的重要内容。传统的路外公共停车场选址方法由于无法实现对停车需求的准确计算,故其对空间位置的选择缺乏科学判断。本文综合考虑路外公共停车场的服务对象及其设置原则,基于位置分配模型,通过城市用地估算和模拟人口分布设定公共停车需求和公共停车设施供给点,并结合城市道路网络,确定城市路外公共停车场的位置、数量以及规模,实现了对路外公共停车场选址规划的优化。最后以潍坊市中心城区为例,对该选址方法予以实证应用。

震后初期应急物流公私协同的动态LAP模型

针对震后初期灾区应急物资严重短缺的现实情况,为满足多主体的不同应急需求,基于公平与效率兼顾的视角,构建满意度最大、总成本最小、人员损失最小的多周期、多目标、多物资的公私物流资源整合的双层动态选址-分配（LAP）模型,上层以商品满足率最大为目标,下层以时间满足率最大为目标;设计遗传算法进行优化求解;最后以汶川地震为例,验证模型和算法的有效性。结果表明：所建模型可以实现震后初期公私物流协同作用下的多物资动态LAP决策,而且兼顾公平和效率。

LaNi_(4.25)Al_(0.75)D_(1.6)中D占位的中子衍射研究

测量了镧基合金氘化物LaNi4.25Al0.75D1.6样品的中子粉末衍射谱,用FULLPROF程序对LaNi4.25Al0.75D1.6的中子衍射数据进行了分析处理,通过对程序参数的拟合,获得了样品的晶胞参数和原子占位及占位数。

应急物资保障系统模糊多目标LARP研究

为了将应急物资快速有效地配送至灾区,从供应链的角度构建一个包含应急物资供应点、集散点、配送中心及受灾点四层结构的应急物资保障系统.在考虑需求不确定性的基础上建立一个双层优化模型.上层模型以最晚运达时间最小、配送总成本最小及车辆载重利用率最大为目标,决策灾区应急物资配送中心的选址及车辆路径安排;下层模型以运输总成本最小为目标,决策应急物资集散点的选址及应急物资的分配.设计一种自适应遗传算法求解上层模型,运用GAMS软件求解下层模型.以'4·20'四川芦山地震应急物资保障为背景构建算例,验证模型和算法的可行性和有效性.

基于LAP-GA的多军事物流配送中心选址

针对传统的多军事物流配送中心选址理论中存在的问题,分析了常用的几种军事物流配送中心选址方法,建立基于LAP-GA的多军事物流配送中心选址模型,利用Matlab数学软件中的遗传算法工具箱(gatool),实现对模型的系统分析和快速求解。结合案例分析,验证模型的正确性和合理性。

多层级防汛应急物资储备库公私协同LAP模型

为实现防汛应急物资多层级储备库的协同布局和储备分配,综合考虑不同等级洪涝灾害的物资需求差异、多物资选址分配策略、多层级出救规则和企业代储点等因素,构建最小化加权总运输时间和系统总成本的储备库公私协同选址-分配模型;设计一个加入多个全局变量的改进非支配排序遗传算法(NSGA-II)对模型进行求解;求解出武汉市各层级储备库选址、储备量和分配关系的最优解集,并对比有无代储点对目标函数带来的影响。结果表明:选址-分配模型能够实现防汛应急物资储备的综合决策,在选择代储点时,物资满足率较为均匀,能避免某种物资出现极度短缺,且能减少时间、降低成本。

Solving DCLAP-MSN based on hybrid genetic algorithm

The dynamic capacitated location allocation problem in the military supportive network（DCLAP-MSN） is a representative of combinative optimization problems,and its optimization process is complicated.For this reason,a dynamic capacitated location allocation model is provided firstly.Then,a hybrid heuristic algorithm which combines genetic algorithm,repair algorithm of solutions and greedy search,is proposed as the solving method.The optimization performance is improved by effectively integrating the repair algorithm of solutions and greedy search with genetic optimization.The experiment results indicate that the proposed algorithm is a feasible and effective method for the problem.

Emerging Water Quality Issues along Rio de la Sabana, Mexico

The basin of Rio de la Sabana is the largest tributary of the Tres Palos coastal lagoon in Southwest Mexico, east of Acapulco. This lagoon and its upstream basin areas have become a high priority area for the preservation of coastal and marine environments. To obtain information about water quality as affected by urban expansion since 2002, fourteen physicochemical parameters (temperature, pH, electrical conductivity, dissolved oxygen, ammonium, nitrate, nitrite, sulphate, phosphate), biochemical (biological and chemical oxygen demand, methylene blue active substances) and bacteriological parameters (total and fecal coliforms) were determined. This sampling was done for dry and rainy season conditions at seven locations (S1, S2, S3, …, S7) along the river, spaced 3 to 6 km apart to a total of 30.4 km. The results were grouped into four zones: (Z1) reference, (Z2) transition, (Z3) polluted, (Z4) recovery. The Alborada (S5) and Tunzingo (S6) sites, adjacent to dense high-class residential areas (Z3), had the greatest pollution charges in both seasons, while the La Poza (S7) site near the Tres Palos lagoon (Z4) showed a decrease in pollution. All parameters correlated with increasing head- to down-river sampling distance by following linear (pH, DO) or curvilinear patterns (all other parameters). Using sampling location and dry versus rainy sampling season as multivariate regression (predictor) variables led to least-squares capturing: 1) 66% to 95% of the T(°C), pH, DO, and PO3-4 variations, and 2) 57% to 96% of the log-linear variations of the other parameters. Among the parameters, T(°C), DO, and PO3-4 were not significantly affected by sampling season, while pH became so after deleting two higher than usual pH values at the S5 and S6 locations during the dry season.

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。