Location of emergency rescue center based on SIR epidemiological model

In view of the pressure time of emergency rescue against the infectious diseases,a mathematical model to optimize the location of emergency rescue centers is proposed.The model takes full account of the spread function of infectious diseases,the cycle of pulse vaccination,the distance between the demand area and the emergency rescue centers,as well as the building and maintenance cost for the emergency rescue center,and so on.At the same time,the model integrates the traditional location selection models which are the biggest cover model,the p-center model and the p-median model,and it embodies the principles of fairness and efficiency for the emergency center location.Finally,a computation of an example arising from practice provides satisfactory results.

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。

Comparison of two theoretical models for electric leak location at landfill

To solve the disability of conventional model used in electrical leak location when measurement electrodes were buried under the liner, a new model of high voltage DC leak detection is developed. For single-liner landfill, the waste material layer, the geomembrane liner and the soil under the liner are simulated with infinite horizontal layers. The leak is regarded as two parts, one being negative current source at the entrance, and the other positive current source of the same size at the exit. Comparisons between the new theoretical model and conventional model show that conventional model is efficient in locating leaks in geomembane liner associating the dipole scanning above the liner but is ineffective when the measurement electrodes were buried under the liner. The new theoretical model data are in excellent agreement with experimental data not only above the liner but also under the liner.

Improvements in seismic event locations in a deep western U.S. coal mine using tomographic velocity models and an evolutionary search algorithm

Methods of improving seismic event locations were investigated as part of a research study aimed at reducing ground control safety hazards. Seismic event waveforms collected with a 23-station three-dimensional sensor array during longwall coal mining provide the data set used in the analyses. A spatially variable seismic velocity model is constructed using seismic event sources in a passive tomographic method. The resulting three-dimensional velocity model is used to relocate seismic event positions. An evolutionary optimization algorithm is implemented and used in both the velocity model development and in seeking improved event location solutions. Results obtained using the different velocity models are compared. The combination of the tomographic velocity model development and evolutionary search algorithm provides improvement to the event locations.

Joint modelling of location and scale parameters of the skew-normal distribution

Joint location and scale models of the skew-normal distribution provide useful ex- tension for joint mean and variance models of the normal distribution when the data set under consideration involves asymmetric outcomes. This paper focuses on the maximum likelihood estimation of joint location and scale models of the skew-normal distribution. The proposed procedure can simultaneously estimate parameters in the location model and the scale model. Simulation studies and a real example are used to illustrate the proposed methodologies.

Using Improved Particle Swarm Optimization Algorithm for Location Problem of Drone Logistics Hub

Drone logistics is a novel method of distribution that will become prevalent.The advantageous location of the logistics hub enables quicker customer deliveries and lower fuel consumption,resulting in cost savings for the company’s transportation operations.Logistics firms must discern the ideal location for establishing a logistics hub,which is challenging due to the simplicity of existing models and the intricate delivery factors.To simulate the drone logistics environment,this study presents a new mathematical model.The model not only retains the aspects of the current models,but also considers the degree of transportation difficulty from the logistics hub to the village,the capacity of drones for transportation,and the distribution of logistics hub locations.Moreover,this paper proposes an improved particle swarm optimization(PSO)algorithm which is a diversity-based hybrid PSO(DHPSO)algorithm to solve this model.In DHPSO,the Gaussian random walk can enhance global search in the model space,while the bubble-net attacking strategy can speed convergence.Besides,Archimedes spiral strategy is employed to overcome the local optima trap in the model and improve the exploitation of the algorithm.DHPSO maintains a balance between exploration and exploitation while better defining the distribution of logistics hub locations Numerical experiments show that the newly proposed model always achieves better locations than the current model.Comparing DHPSO with other state-of-the-art intelligent algorithms,the efficiency of the scheme can be improved by 42.58%.This means that logistics companies can reduce distribution costs and consumers can enjoy a more enjoyable shopping experience by using DHPSO’s location selection.All the results show the location of the drone logistics hub is solved by DHPSO effectively.

A skew–normal mixture of joint location, scale and skewness models

Normal mixture regression models are one of the most important statistical data analysis tools in a heterogeneous population. When the data set under consideration involves asymmetric outcomes, in the last two decades, the skew normal distribution has been shown beneficial in dealing with asymmetric data in various theoretic and applied problems. In this paper, we propose and study a novel class of models： a skew-normal mixture of joint location, scale and skewness models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The issues of maximum likelihood estimation are addressed. In particular, an Expectation-Maximization （EM） algorithm for estimating the model parameters is developed. Properties of the estimators of the regression coefficients are evaluated through Monte Carlo experiments. Results from the analysis of a real data set from the Body Mass Index （BMI） data are presented.

Modeling the criminal's location choices in urban areas

With the method of dynamic programming, two spatial variables,the expected utility and the probability of success of each crime, are used to model the criminal's location choices in urban areas in this paper.The modeling results show that a criminal optimizes his crime locations according to the expected utility and the success probability during his planned period A criminal usually commits his first offense in the district that has the highest probability of success but a lower expected utility, and commits his last crime in the district where the expected utility is the highest and success probability is lower.If a location has both an expected utility and a higher probability of success, the criminal might commit all his offenses in thes place. The model also suggests that crime prevention measures should be adopted in accordance with local conditions. 'Covering' measures, such as patrolling, should be taken in the poor residential districts or juvenile delinquency districts, while more sophisticated and advanced measures should be introduced in the richer districts or the districts where professional criminals haunt.

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.

Accurate Fault Location Modeling for Parallel Transmission Lines Considering Mutual Effect

:A new accurate algorithms based on mathematical modeling of two parallel transmissions lines system(TPTLS)as influenced by the mutual effect to determine the fault location is discussed in this work.The distance relay measures the impedance to the fault location which is the positive-sequence.The principle of summation the positive-,negative-,and zero-sequence voltages which equal zero is used to determine the fault location on the TPTLS.Also,the impedance of the transmission line to the fault location is determined.These algorithms are applied to single-line-to-ground(SLG)and double-line-to-ground(DLG)faults.To detect the fault location along the transmission line,its impedance as seen by the distance relay is determined to indicate if the fault is within the relay’s reach area.TPTLS under study are fed from one-and both-ends.A schematic diagrams are obtained for the impedance relays to determine the fault location with high accuracy.

Vehicle Real-time Location Based on Visual Perception Model

Vehicle recognition system (VRS) plays a very important role in the field of intelligent transportation systems.A novel and intuitive method is proposed for vehicle location.The method we provide for vehicle location is based on human visual perception model technique. The perception color space HSI in this algorithm is adopted.Three color components of a color image and more potential edge patterns are integrated for solving the feature extraction problem.A fast and automatic threshold technique based on human visual perception model is also developed.The vertical edge projection and horizontal edge projection are adopted for locating left-right boundary of vehicle and top-bottom boundary of vehicle, respectively. Very promising experimental results are obtained using real-time vehicle image sequences, which have confirmed that this proposed location vehicle method is efficient and reliable, and its calculation speed meets the needs of the VRS.

Solution and simulation algorithm of microseismic events location to three-dimensional model by comprehensive location method based on Matlab

The essential for microseismic monitoring is fast and accurate calculation of seismic wave source location. The precision of most traditional microseismic monitoring processes of mines, using TDOA location method in two-dimensional space to position the microseismic events, as well as the accuracy of positioning microseismic events, may be reduced by the two-dimensional model and simple method, and ill-conditioned equations produced by TDOA location method will increase the positioning error. This article, based on inversion theory, studies the mathematical model of TDOA location method, polariza- tion analysis location method, and comprehensive difference location method of adding angle factor in the traditional TDOA location method. The feasibility of three methods is verified by numerical simulation and analysis of the positioning error of them. The results show that the comprehensive location method of adding angle difference has strong positioning stability and high positioning accuracy, and it may reduce the impact effectively about ill-conditioned equations to positioning results. Comprehensive location method with the data of actual measure may get better positioning results.

The Dynamic Location Model to Consider Background Traffic

This study concerns to the determination of location of freight distribution warehouses. It is part of a series of research projects on a distribution system we developed to deal with cases in a public service obligation state-owned company (PSO-SOC). This current research is characterized by the consideration of background traffic of the entire time period of planning rather than one certain time target on location model. It is aimed that the location decision to be more applicable and accommodative to the dynamic of the traffic condition. Once the decision is implemented, it will give the best outcome for the entire time period, not only for the initial time, end time or certain time of time period. A heuristic approach is proposed to simplify complexity of the model and network representation technique is applied to solve the model. A hyphotetical example is discussed to illustrate the mechanism of finding the optimal solution in term of both its objective function and applicability.

Terminal Location Models for Intermodal Transport Network Optimization

Since rail-road transport uses road and rail networks and requires the transshipment infrastructures at the terminals, its competitiveness depends not only on the costs but also on the location of these terminals. This paper focused on providing a methodology for determining the optimal locations for intermodal freight transportation terminals in consolidation network. The goal is to minimize total costs in order to increase the efficiency of the transportation system. This paper also has allowed us to have an overview of the methods and models that exist for solving the problem of intermodal and terminal locating.

Improved Secure Trust-based Location-Aided Routing Model for MANETs

In view of the security weakness in resisting the active attacks by malicious nodes in mobile ad hoc networks,the trust metric is introduced to defend those attacks by loading a trust model on the previously proposed Distance-Based LAR.The improved Secure Trust-based Location-Aided Routing algorithm utilizes direct trust and recommendation trust to prevent malicious nodes with low trust values from joining the forwarding.Simulation results reveal that ST-LAR can resist attacks by malicious nodes effectively;furthermore,it also achieves better performance than DBLAR in terms of average end-to-end delay,packet delivery success ratio and throughput.

Variable selection for skew-normal mixture of joint location and scale models

Although there are many papers on variable selection methods based on mean model in the nite mixture of regression models,little work has been done on how to select signi cant explanatory variables in the modeling of the variance parameter.In this paper,we propose and study a novel class of models:a skew-normal mixture of joint location and scale models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population.The problem of variable selection for the proposed models is considered.In particular,a modi ed Expectation-Maximization(EM)algorithm for estimating the model parameters is developed.The consistency and the oracle property of the penalized estimators is established.Simulation studies are conducted to investigate the nite sample performance of the proposed methodolo-gies.An example is illustrated by the proposed methodologies.

Comparative Geospatial Planning Model for “Location Specific” Intervention and Continuous Improvement Strategy

Sustainable development can only be achieved by conscious planning and implementation of action plans. Decision making requires a careful selection of the right conceptual framework and models for planning and implementation processes. Planning process models dictate in very clear terms what must be done and how it is done to achieve a successful completion of a process of activity [1]. Since about 80% of data used to support decisions are geographically related [3], it is necessary to put Geographic Information Systems (GIS) at the core of the planning and implementation model. There exists a great disparity in a heterogeneous world. The locational disparity in achieving sustainable development, therefore, necessitates a planning model that is “location specific” i.e. identifies areas (locations) requiring intervention and areas (locations) requiring continuous improvement strategies. This was achieved in this study by reviewing Bell’s Information System Strategic Planning Model and Kaufman’s Strategic Planning Model, and the designing of new model to overcome the limitation of existing models. Practical application of the new model was carried out in education planning and administration in order to achieve the global goals for sustainable development 4 (quality education). Finding shows that the Comparative Geospatial Planning Model for “Location Specific” Intervention and Continuous Improvement Strategy is useful to support the achievement of sustainable development goals in multidisciplinary, multi-sector applicable instances.

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.

Collaborative planning approach for anti-bioterrorism emergency facility location based on aerodynamics

To smooth the correlation process from bio-virus diffusion to emergency relief response,the Gaussian plume model is used to describe the diffusion of dangerous sources,where the bio-virus concentration at any given point in affected areas can be calculated.And the toxic load rule is introduced to define the borderline of the dangerous area at different levels.Combined with this,different emergency levels of different demand points in dangerous areas are confirmed using fuzzy clustering,which allows demand points at the same emergency level to cluster in a group.Some effective emergency relief centers are chosen from the candidate hospitals which are located in different emergency level affected areas by set covering.Bioterrorism experiments which were conducted in Nanjing,Jiangsu province are simulated,and the results indicate that the novel method can be used efficiently by decision makers during an actual anti-bioterrorism relief.

Spatial Evolution and Locational Determinants of High-tech Industries in Beijing

Using datasets on high-tech industries in Beijing as empirical studies, this paper attempts to interpret spatial shift of high-tech manufacturing firms and to examine the main determinants that have had the greatest effect on this spatial evolution. We aimed at merging these two aspects by using firm level databases in 1996 and 2010. To explain spatial change of the high-tech firms in Beijing, the Kernel density estimation method was used for hotspot analysis and detection by comparing their locations in 1996 and 2010, through which spatial features and their temporal changes could be approximately plotted. Furthermore, to provide quantitative results, Ripley′s K-function was used as an instrument to reveal spatial shift and the dispersion distance of high-tech manufacturing firms in Beijing. By employing a negative binominal regression model, we evaluated the main determinants that have significantly affected the spatial evolution of high-tech manufacturing firms and compared differential influence of these locational factors on overall high-tech firms and each sub-sectors. The empirical analysis shows that high-tech industries in Beijing, in general, have evident agglomeration characteristics, and that the hotspot has shifted from the central city to suburban areas. In combination with the Ripley index, this study concludes that high-tech firms are now more scattered in metropolitan areas of Beijing as compared with 1996. The results of regression model indicate that the firms′ locational decisions are significantly influenced by the spatial planning and regulation policies of the municipal government. In addition, market processes involving transportation accessibility and agglomeration economy have been found to be important in explaining the dynamics of locational variation of high-tech manufacturing firms in Beijing. Research into how markets and the government interact to determine the location of high-tech manufacturing production will be helpful for policymakers to enact effective policies toward a more efficient urban spatial structure.