A simulation model for evaluating a set of emergency vehicle base locations: development, validation, and usage.

This paper describes our experiences in developing a simulation model for evaluating a set of emergency response vehicle base locations. The project was undertaken jointly by the University of Arizona and the Tucson Fire Department. The issues of model development, data collection, model validation, and experimentation are discussed. The critical nature of the problem and the clients' lack of experience with mathematical models, made model validation the major step in gaining user acceptance. We show that looking solely at standard performance statistics such as the calls successfully serviced, may lead to the acceptance of an invalid model. We also show that the high level of detail used in many simulation models for evaluating base locations is unnecessary in the current case. An analysis evaluating two alternative sets of locations for the Tucson system is discussed.     

战略性工业结构转变——陕北能源资源转化的路径新选择

陕北拥有丰富的能源资源,但现有工业结构布局不合理,不能充分地将这种资源优势转化为经济优势。本文结合产业经济学、产业布局学相关理论和陕北实际情况,提出陕北区域战略性工业结构布局转变设想,并对其必要性、利弊条件、实施原则以及合理布局等进行分析,希望能通过陕北区域战略性工业结构布局的转变来加快推进陕北地区能源资源转化。     

Incorporating activity space and trip chaining into facility siting for accessibility maximization

Location models have been widely used to support locational decisions for various service provision. One common objective of location models has been to ensure maximal accessibility of sited facilities to demand populations. Accessibility evaluation in location models often assumes that trips originate from fixed locations (usually home) and are single purpose. These assumptions contradict the empirical evidence that suggests trips also commonly originate from non-home locations and may involve multiple stops. In this study, a new multi-objective location model is developed that extents the classic p-median problem (PMP) to account for a more realistic assessment of accessibility. Based on the individual accessibility assessment, notions of trip chaining and activity space are incorporated into the model development. In addition to fixed home locations, stops along chained trips are allowed for potential service site visits, and activity space is introduced as an additional dimension to evaluate accessibility of alternative opportunities. The effectiveness of the new model is demonstrated using an application in Tucson, AZ.     

Data center supply chain configuration design: A two-stage decision approach

Data centers are special-purpose facilities that enable customers to perform cloud based real-time online transactions and rigorous computing operations. Service levels of data center facilities are characterized by response time between query and action, which to a large extent depends on data center location and data travel distance. Another aspect of service level is resource up-time availability, which is determined by data center configuration. Data center location and configuration decisions are, therefore, of great significance to ensure uninterrupted operations in customers of manufacturing and service industries relying on cloud-based computing resources. In this study, following a grid-based location approach, we present two mixed integer linear programming models for capacitated single-source data center location-allocation problems. The first model provides optimal locations, capacities and configurations of data centers, and allocation of demands to open facilities when there is no existing facilities in the region. Our second model considers the decision problem of meeting new demand when the existing demand is met by the already opened facilities. We term these newly arrived demand as replication demand, which results either from emergence of new users of existing customers at distant locations in the future, or as a means of increasing data resilience by creating data replication as a backup. To solve the decision problem for meeting primary and replication demand optimally, we propose a two-stage decision algorithm. The algorithm provides optimal locations, capacities and configurations for new data centers, capacity addition decisions to the existing facilities and subsequent allocation of demands. Both models and solution algorithm are implemented using AMPL programming language and solved with CPLEX solver. The models are found to be scalable and capable to provide high quality solutions in reasonable time.     

Improving access to health facilities in Nouna district,Burkina Faso

The Nouna health district in Burkina Faso, has a population of approximately 275,000 people living in 281 villages, and is served by 25 health facilities, as of 2006. For many people, the time and effort required in traveling to a health facility, which may demand a journey of many kilometers over poor roads on foot, is a deterrent to seeking proper medical care. In this study we examine how access to health facilities in Nouna may be improved by considering the configuration of the road network in addition to the locations of the facilities. We model the situation as a facility location–network design problem and draw conclusions about how best to improve the physical access of the health facilities. Our model shows the extent to which access can be improved when the road network is considered along with facility locations, in contrast to facility locations considered alone.     

On the Optimal Structure of Government Subsidies for Enterprise Zones and Other Locational Development Programs

Government locational development programs often reward businesses for decisions they would have made or that are going to be quickly reversed. This paper presents a model to determine the amount and structure of government locational subsidies that minimize this problem. We model the firm's decision to switch locations as an option whose value depends on stochastic operating costs, the costs to switch locations and subsidies offered by the government. The government maximizes the expected benefit from the operation of the firm within its preferred location by choosing a subsidy package that explicitly and endogenously recognizes the firm's switching option.     

Dynamic vehicle routing with anticipation in disaster relief

Pickup and delivery problems (PDP), where locations may both receive and send goods, are an extension of the classical vehicle routing problem. This paper considers the application of a routing and scheduling problem for forwarding agencies handling less-than-truckload freight in disasters. The approach evaluates the benefits of dynamic optimization anticipating varying travel times (i.e., the availability of connections in this case) as well as unknown orders (i.e., the integration of demand regions on short-notice) in the specific environment of emergencies. The objective is to avoid delays and increase equipment utilization. We model a multi-stage mixed integer problem which is able to operate under variable demand and transport conditions.     

Modeling integrated supply chain logistics in real-time large-scale disaster relief operations

The goal of this research is to develop a comprehensive model that describes the integrated logistics operations in response to natural disasters. We propose a mathematical model that controls the flow of several relief commodities from the sources through the supply chain and until they are delivered to the hands of recipients. The structure of the network is in compliance with FEMA's complex logistics structure. The proposed model not only considers details such as vehicle routing and pick up or delivery schedules; but also considers finding the optimal locations for several layers of temporary facilities as well as considering several capacity constraints for each facility and the transportation system. Such an integrated model provides the opportunity for a centralized operation plan that can eliminate delays and assign the limited resources to the best possible use.A set of numerical experiments is designed to test the proposed formulation and evaluate the properties of the optimization problem. The numerical analysis shows the capabilities of the model to handle the large-scale relief operations with adequate details. However, the problem size and difficulty grows rapidly by extending the length of the operations or when the equity among recipients is considered. In these cases, it is suggested to find fast solution algorithms and heuristic methods in future research.     

Mathematical analysis of emergency ambulance location

Proper ambulance location is crucial in saving lives and reducing injury. To determine efficient and effective locations, it is necessary to evaluate both the spatial and temporal distributions of demand. Because of the complex nature of the ambulance response and transport activities, the problem is subdivided into a facility location problem and a vehicle allocation problem. A set covering model is modified to solve the location problem while a simulation is used to solve the allocation problem. Combining these two models provides a powerful methodology for systematically finding a satisfactory solution to the ambulance location problem.     

Optimization of the facility location-allocation problem in a customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional cost-based approach.     

带多个变点的逐段连续线性分位数回归模型及应用

研究目标：建立具有多个变点的逐段连续线性分位数回归模型（Continuous Piecewise Linear Quantile Regression with Multiple Change Points,CPLQR）。研究方法：先通过LASSO和广义贝叶斯信息准则确定变点个数,再通过线性化技巧来估计变点的位置与回归系数。研究发现：新方法能够同时确定变点个数、估计变点位置和回归系数,而且具有较强的稳健性;应用该方法于年龄和身体质量指数之间关系,进一步证实了模型的实用性。研究创新：新方法能够处理多个变点的问题,通过LASSO和广义贝叶斯信息准则确定变点数目,避免了主观判断的弊端;借助线性化技巧,解决了目标函数在变点处不可导问题。研究价值：本文结果将为分析经济、金融、医药和生物等学科中存在结构变化的数据提供强有力的研究工具。     

Wages, Welfare Benefits and Migration

Differences in economic opportunities give rise to strong migration incentives, across regions within countries, and across countries. In this paper we focus on responses to differences in welfare benefits across States. We apply the model developed in Kennan and Walker (2008), which emphasizes that migration decisions are often reversed, and that many alternative locations must be considered. We model individual decisions to migrate as a job search problem. A worker starts the life-cycle in some home location and must determine the optimal sequence of moves before settling down. The model is sparsely parameterized. We estimate the model using data from the National Longitudinal Survey of Youth (1979). Our main finding is that income differences do help explain the migration decisions of young welfare-eligible women, but large differences in benefit levels provide surprisingly weak migration incentives.     

A multiobjective modeling approach to locating incinerators

The location of hazardous material incineration facilities is an important problem due to the environmental, social, and economic impacts that they impose. The costs associated with the facilities and the risks placed on nearby populations are important concerns as are the distributions of these costs and risks. This paper introduces a mixed-integer, multiobjective programming approach to identify the locations and capacities of such facilities. The approach incorporates a Gaussian dispersion model and a multiobjective optimization model in a GIS-based interactive decision support system that planners can access via the Internet. The proposed approach is demonstrated via a case study in central Portugal where the national government has decided to locate a large facility for the incineration of hazardous industrial waste. Due to intense local and national opposition, construction of the facility has been delayed. The system has been designed so that it can be used by decision makers with no special training in dispersion modeling, multiobjective programming, or GIS.     

A Hybrid model for locating new emergency facilities to improve the coverage of the road crashes

We propose an emergency facility-locating model aimed at increasing the coverage of emergency demand throughout the city. The proposed model takes into account the status and location of the emergency facilities in the network and identifies locations suitable for the construction of new facilities. Here, Data Envelopment Analysis (DEA) and Maximum Coverage Location Problem (MCLP) have been combined in a single model. To do so, design problem and evaluation problem are considered concurrently to maximize the efficiency of services provided by emergency facilities across the city in response to the demand. Moreover, the total emergency demand in each district was considered in relation to the population density, the fatal, injurious, and property damage only (PDO) crashes. The coverage area of each emergency facility was assumed to be proportional to the average ambulance speed in the surrounding road network during rush hours. The available budget was included in the model to let the model function under various fiscal conditions. Model input variables consisted of average number of mortalities, injuries and PDO crashes as well as the population density of each urban district. The output variables of the model included the coverage share of proposed emergency centers and hospitals equipped with ambulances. The model was tested on the network of Tehran (Iran). It is recommended to add the location of some emergency centers and hospitals to the network. Moreover, the results showed that ten urban districts had efficiency problem in provision of emergency services.     

Location choice for direct foreign investment in new hospitals in China by using ANP and TOPSIS

This study models location choices for foreign direct investments in new hospitals in China as an multi-criteria decision-making (MCDM) problem and designs develops a multidirectional relationship decision model combines the techniques of analytic network process (ANP) and technique for order performance based on similarity to the ideal solution (TOPSIS). This study discusses applying ANP to the relative weighting of multiple assessment criteria. The TOPSIS approach is employed to rank 15 counties without the Zhoushan of China’s Yangtze River Delta (YRD) region in terms of their overall performance under the decision model. To illustrate how the proposed approach is applied to the problem of selecting locations for new hospitals in China an empirical study of a real case is performed. This study demonstrates the effectiveness and feasibility of the proposed assessment procedure.     

配送中心选址的遗传算法研究

针对配送中心的选址问题,将遗传算法这一全局搜索优化技术运用其中,通过建立选址的遗传算法模型,研究了算法设计,分析了其特点,并与传统的混合整数规划解法进行了分析比较。     

A hybrid multi-criteria decision making approach for strategic retail location investment: Application to Turkish food retailing

Retail location selection decision is a critical and complex process which requires the evaluation and aggregation of multiple criteria and also the usage of appropriate data related to them. This study handles the problem at a strategic level and proposes a Monte Carlo simulation based multi-criteria strategic location decision model for food retailing. This model integrates two multi-criteria decision making (MCDM) methods which are Hesitant Analytic Hierarchy Process (H-AHP) and Grey Relational Analysis (GRA) methods. Firstly, H-AHP method is used to obtain the weights of criteria to be used in GRA based on the experts' judgements. Secondly, simulation based GRA is used for ranking the alternative locations. Finally, the effectiveness and the applicability of the proposed model is illustrated with an application of strategic location investment decision of food retail stores in Turkey.     

Improving accessibility to rural health services: The maximal covering network improvement problem

Accessibility to health facilities is a critical factor in effective health treatment for people in rural areas of lesser-developed countries. In many areas accessibility is diminished by the lack of all-weather roads, making access subject to weather conditions. Location-allocation models have been used to prescribe optimal configurations of health facilities in order to maximize accessibility, but these models are based on the assumption that the underlying transport network is static and always available. Essentially, past work has ignored the potential impacts of improvements to the transport system in modeling access. In this paper we propose a model that treats the opposite side of the location/transport equation; that is, a model that treats existing facility locations as fixed and improves health service accessibility by upgrading links of the transport network to all-weather roads. This new model, called the Maximal Covering Network Improvement Problem (MC-NIP) is formulated as an integer-linear programming problem. An application of the MC-NIP model to the Suhum District of Ghana is presented, which shows that even a modest level of road improvement can lead to substantial increases in all-season access to health service.     

Facility location under demand uncertainty: Response to a large-scale bio-terror attack

In the event of a catastrophic bio-terror attack, major urban centers need to efficiently distribute large amounts of medicine to the population. In this paper, we consider a facility location problem to determine the points in a large city where medicine should be handed out to the population. We consider locating capacitated facilities in order to maximize coverage, taking into account a distance-dependent coverage function and demand uncertainty. We formulate a special case of the maximal covering location problem (MCLP) with a loss function, to account for the distance-sensitive demand, and chance-constraints to address the demand uncertainty. This model decides the locations to open, and the supplies and demand assigned to each location. We solve this problem with a locate-allocate heuristic. We illustrate the use of the model by solving a case study of locating facilities to address a large-scale emergency of a hypothetical anthrax attack in Los Angeles County.     

高铁施工材料物流中心选址研究

针对京沪线施工材料供应过程中的实际情况,以钢轨为例,分析其物流模式,引入了0-1整数规划,建立了中转站的选址模型。在建模时,考虑到了需求连续问题,用离散的可以确定位置的施工点的需求来近似连续需求,从而将连续需求问题离散化,最后用MATLAB软件对问题进行求解。