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.     

Integrated fire and ambulance siting: A deterministic model

The model presented in this paper is developed for an integrated emergency system in which ambulance and fire service deployment are simultaneously considered. The model extends and blends the Maximal Covering Location Problem (MCLP) for ambulance siting and the Facility Location-Equipment Emplacement Technique (FLEET) for fire service placement. The objective of the new formulation is to maximize and trade-off both ambulance and fire coverage subject to constraints on the total number of vehicles and stations of both types that can be sited. We introduce a new concept in integrated coverage that permits free-standing ambulance stations to be sited in addition to fire stations. Typically, ambulances are located at fire stations and, sometimes, hospitals; that is, eligible sites are driven by prior choices that did not include consideration of ambulance service. Our results, based on three sample problems, suggest that, for a given budget level for facility construction, it may be possible for ambulance coverage to be increased with little or no loss in fire coverage. This condition pertains if ambulance stations are freed of the requirement to be sited only at fire stations.     

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.     

Epidemics,labour markets and unemployment: the impact of SARS on human resource management in the Hong Kong service sector

This article examines the links between epidemics and their economic consequences, specifically in terms of their impacts on labour markets and jobs. To exemplify the above, we examine the effects of SARS (Severe Acute Respiratory Syndrome) on the Hong Kong economy, its labour market and its level of employment and unemployment. The article hypothesizes that the greatest impact would be on human resource management (HRM) in the service industries and on particular sub-sectors, such as the hotel sector. It concludes that the dramatic demand and supply ‘shocks’ significantly affected both the demand for and the supply of labour in the sector, with discernible HRM consequences.     

The impact of SARS on China's human resources: implications for the labour market and level of unemployment in the service sector in Beijing,Guangzhou and Shanghai

In this paper, we examine the effects of SARS (Severe Acute Respiratory Syndrome) on China's human resources, its labour-market and its level of employment and unemployment, looking specifically at what was one of its economically most vulnerable points, the hotel industry. The paper hypothesizes that the greatest impact would be on human resources in the service-industries and on particular sub-sectors, such as employment in hotels, located in three main cities in the PRC, in Beijing, Guangzhou and Shanghai, catering to both overseas as well as domestic tourism. It tentatively concludes that the almost dramatic demand and supply ‘shocks’ may have directly affected both the demand for and the supply of labour in the sub-sector, with discernable employment consequences.     

Application and extension of the Moore and ReVelle Hierarchical Maximal Covering Model

In a paper published in Management Science in 1982, George Moore and Charles ReVelle proposed a location model for siting a hierarchical system of medical facilities. In this paper we apply the Moore and ReVelle Hierarchical Maximal Covering Model to the location of medical facilities in the Kohat district in Pakistan. Optimal solutions of the Moore and ReVelle model are compared against the actual location of medical facilities in this district. We then extend the Moore and ReVelle formulation to include fixed and variable costs for siting and operating the facilities. We compare the solutions of that formulation with the results of the original Moore and ReVelle model.     

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.     

Intervention analysis of SARS on Japanese tourism demand for Taiwan

Japan was Asia’s leading generator of international tourism in the 1980s and 1990s. Japanese tourists make up over 30% of all international tourists to Taiwan and they have been the highest ranking tourist source market since the early stages of the island’s tourism development in the 1970s. However, the Severe Acute Respiratory Syndrome (SARS) outbreak in 2003, the most catastrophic disaster in the past 100 years in Taiwan, had a huge impact on Japanese inbound tourism to the island. The purpose of this study is to evaluate how Japanese inbound arrivals have been affected by the SARS outbreak. A SARIMA with intervention model is used to assess the impact of the epidemic on inbound tourism from Japan to Taiwan in the aftermath of the SARS outbreak. The empirical results indicated that inbound tourism from Japan was devastated by the crisis, particularly during the first 5 months after the SARS outbreak. This study provides some helpful insight for the tourism industry to respond to the impact of exogenous shock.     

城市可达性研究的理论与方法评述

首先探讨了可达性的涵义与主要特征.其次综合可达性的主要定量评价方法,对各种方法的优缺点进行比较,并总结了近期可达性评价方法的进展情况.最后对可达性研究中存在的问题进行了探讨.     

Planning for equal transit-based accessibility of healthcare facilities: A case study of Shenzhen,China

Recent location-allocation studies have made considerable progress in optimizing the equality of facility accessibility but are focused on automobile transport to facilities. In cities, however, the transit-based accessibility of essential services is crucial for social equality and sustainable development. In this study, we develop a modified transit-based maximal accessibility equality (MAE) model for optimizing the equality of the transit-based accessibility of healthcare facilities. In this model, equality is quantified as the weighted mean absolute deviation (WMAD) of accessibility across locations. Two scenarios are set up to reallocate resources or allocate newly added resources. The results reveal that the equality of transit-based healthcare accessibility can be significantly improved in both scenarios. A dispersed planning strategy for facilities is suggested to achieve equal accessibility. However, the transit-based optimization results significantly differ from the car-based optimization results, with more supply allocated to facilities close to transit corridors. This finding implies that the traditional car-based MAE model might generate unequal healthcare accessibility for transit-dependent populations and thus lead to biased recommendations for healthcare planning. Furthermore, it shows that traditional car-based optimization may engender a misallocation of healthcare supply, exacerbating the inequality in healthcare accessibility. The necessity of incorporating public transit into public facility planning is highlighted. The improved MAE model can be applied in cities where the supply of public services is relatively adequate and public transit plays an important role in daily mobility.     

Location of manufactured housing and its accessibility to community services: a GIS-assisted spatial analysis

This paper investigates the location and accessibility disadvantages of manufactured housing using Geographical Information Systems. It is found that, on an aggregated basis, manufactured housing has been placed further away from positive public-community facilities and, hence, services than other types of housing. It has also been placed further away from major employment centers. Moreover, a higher percent of such housing has been placed in flood zones. On the other hand, manufactured housing has not been placed closer to large negative facilities, such as landfill sites, heavy industrial or manufacturing plants, or airports. These findings reinforce the claim that manufactured housing faces selected zoning barriers or restrictions.     

模型算法在企业的场址选择及其内部设施的平面布置中的应用

企业的场址选择及其内部设施的平面布置形式，对于企业的运输费用具有举足轻重的作用。本文对企业和内部设施的布置进行模型设计，并通过层次分析法对场址选择方案进行比选．采用对目标函数的优化对企业内部设施的平面布置形式进行优化。     

对房屋基础渗漏原因及解决措施的分析

房屋渗漏问题不仅影响到居民的正常生活,也会造成建筑隐患和缩短建筑使用寿命。因此,分析渗漏原因,对症下药,解决这些建筑物的渗漏问题,延长其使用期限,具有重要的意义。     

Reconfiguring a set of coverage-providing facilities under travel time uncertainty

We study networks of facilities that must provide coverage under conditions of uncertainty with respect to travel times and customer demand. We model this uncertainty through a set of scenarios. Since opening new facilities and/or closing existing ones is often quite expensive, we focus on optimal re-configuration of the network, that is finding a facility set that achieves desired thresholds with respect to expected and minimal coverage, while retaining as many of the existing facilities as possible. We illustrate our model with an example of Toronto Fire Service. We demonstrate that relocating just a few facilities can have the same effect as opening a similar number of new ones. We develop exact and approximate solution approaches and test them with computational experiments. Algorithm based on Tabu Search (with certain novel components) appears to be particularly successful for this problem. We also analyze the multi-objective version of the problem, where the expected and minimum coverage levels are treated as objectives in addition to the objective of maximizing the number of pre-existing facilities in the final location set.     

Critical infrastructure location under supporting station dependencies considerations

This paper develops a framework to locate critical infrastructure (CI) facilities to most fully capitalize on the supporting stations (SSs) they depend on for normal operation. CI facilities include health services, transportation and electricity; agencies that impact the national economy, security and the public's health and wellbeing. SSs are facilities that provide essential services for the regular operation of a CI. For instance, the power service, communication services and water supply services are SSs for Hospitals. In this paper SSs are independent from the CIs that they service and have a heterogeneous probability of failure that will cripple the dependent CI. The proposed framework ranks the SS according to its cost of providing service such that the rank-1 SS is the primary service provider and incorporates the probability of failure for the SS. The CI will be served from secondary SS if the primary fails due to a disaster. This formulation insures the continuous service to the CI from SS and determines both the optimal location of the CI and the optimal number of demands served. A mixed integer linear programming approach is applied to develop a Reliable Facility Location Problem considering Supporting Stations (RFLP-SS) to identify the optimal location to build a critical facility. In addition to that, The RFLP-SS determines the capacity of the optimally located facility and its allocated demands. This research highlights the importance of considering dependencies among the SSs that service CI. The paper presents a case study in Puerto Rico to demonstrate the applicability of the proposed framework. The case study investigates the status of health services in Puerto Rico, and identifies the optimal locations to establish new hospitals. The paper recommends 11 locations for new hospitals so that the people of Puerto Rico will be better served than they are currently.     

Global human development: accounting for its regional disparities

This study’s multilevel statistical models quantify the effects of civilization zones and instrumental factors on the capacities for human agency that a country provides its citizens. These capacities are measured by the UN’s human development index, which synthesizes measures of literacy, longevity, and income. Indicators of political democracy, slavery, national debt, corruption, and internal conflict gauge the instrumental factors. Political freedom and emancipative employment coupled with civil order account for the regional differences in human development scores; civilization zones, heavily indebted poor countries, and corruption influence the variability among countries within the regions.     

Physical accessibility as a social indicator

A discussion is presented of the ways in which accessibility to employment and urban services constitute an important measure of the quality of urban living, and how accessibility might, therefore, be included as an important component of a “social report” for a city or region. A conceptual framework is introduced for measuring accessibility in terms of the ease with which citizens may reach a variety of opportunities for employment and services. This framework is interpreted as an approach to evaluating transportation and regional plans which differs from approaches based upon travel volumes and travel times which are currently employed in urban transportation planning and evaluation. The use of the proposed measures of accessibility is illustrated with data on accessibility to employment and health care facilities in Los Angeles, and these data are interpreted to illustrate differences in accessibility as a function of spatial location of residence, and socio-economic status.     

Accurate estimation of expected coverage: revisited

As noted in several studies (Batta et al., Transp. Sci. 23 (1989) 277), (Burwell et al., Comput. Opns. Res. 20 (1993) 113), (Daskin, Network and Discrete Location, Wiley, New York, 1995), (Marianov and ReVelle, Eur. J. Opns. Res. 93 (1996) 110), (Saydam et al., Socio-Econ. Plann. Sci. 28(2) (1994) 113), the accurate estimation of expected coverage is an important and open issue. Although the maximum expected coverage model is empirically shown to prescribe a robust set of “optimal” locations, earlier findings suggest that it could also over or underestimate the coverage by a significant margin. In this study, we present a genetic algorithm (GA) that combines the expected coverage approach with the hypercube model (Jarvis, Mgmt. Sci. 31 (1985) 235), (Larson, Comput. Opns. Res. 1 (1974) 67), (Larson, Opns. Res. 23 (1975) 845) to solve the maximum expected coverage location problem with increased accuracy and realism. Our findings suggest that the GA provides at least as good solutions 94% of the time making it a viable alternative to the two-step procedures stipulated earlier.     

Signed social structure optimization for shift assignment in the nurse scheduling problem

This paper develops a mathematical framework that relies on modern social network analysis theories for treating the nurse team formation and nurse scheduling (shift assignment) problems, accounting for signed social connections. These problems lie in assigning nurses to teams/shifts such that the constraints regarding both the working regulations and nurses preferences are satisfied. Recent research indicates the dependence of nursing team performance on team social structure; however, so far, the social structure considerations have not been explicitly incorporated into the mathematical formulations of the nurse scheduling problem. The presented framework introduces models that quantitatively exploit such dependence. This paper explores instances of Nurse Team Formation Problem (NTFP) and Nurse Scheduling Problem (NSP) incorporating signed social structure with the measures based on such network structures as edges, full dyads, triplets, k-stars, balanced and unbalanced triangles, etc., in directed, signed networks. The paper presents the integer programming formulations for NTFP and NSP, and a problem-specific heuristic that performs variable-depth neighborhood search to tackle NTFP instances with signed social structures. Computational results for a real-world problem instance with 20 nurses are reported. The insights obtained from the presented framework and future research directions are discussed.