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This research is conducted with the aim of proposing an integrated mathematical model for backup facilities in the area of accommodation and supply in case of flood disaster. We consider a combination of supportive strategies, such as construction primary and backup facilities, equipment and additional allocation to increase reliability of humanitarian logistics. A multi-objective, multi-period, and multi-scenario model is proposed to locate and allocate facilities in two preparation and response phases. In the developed model, the cost fluctuations are minimized via identifying Conditional Value at Risk (CVaR) as the objective function. Further, every decision-maker is capable of managing a percentage of long-term risks by adopting their confidence level. This model can also affect the recovery phase by using supportive strategies. In the proposed hybrid solution approach, the location-allocation criteria in the humanitarian logistics are classified based on their most related solution method. Thus, all the effective criteria are taken into account, and less important criteria are excluded. Given the safety criteria, a Geographic Information System (GIS) is also considered in this model. Finally, after conducting sensitivity analysis on supportive strategies like backup facilities strategy, management solutions are suggested to significantly decrease the severity and amount of disaster damages. The results reveal that backup facilities have an effective role in increasing the reliability of the chain, which can be greatly increased by combining with other supportive strategies. Also, adding the CVaR measure while considering scenarios with a low probability of occurrence and high impact, will reduce costs. The results show that the final model can reduce the costs by an average of 52%. [ABSTRACT FROM AUTHOR]

The equitable allocation of public service facilities is directly related to the healthy development and socially just functioning of cities. Traditional location-allocation models mostly take travel distance and facility construction cost as the decision-making objectives, with relatively single optimization objectives, and are not sufficiently adaptable to reality. The introduction of the accessibility analysis and the concept of equalization of public services diversify the objectives of urban public service facility optimization decisions. The construction of the circle of life is based on residents' behavior and helps to improve its adaptability in the configuration of public services. This study evaluates the accessibility of eight types of public service facilities in Xiangyang High-tech Zone, China, from a Living Circle perspective, based on the Gaussian Two-step Floating Catchment Area (G2SFCA) method. We integrate the advantages of the Minimum Facility Point (MFP) model, Maximum Covering Location Problem (MCLP) model, and P-Median model to address the equity and efficiency issues in facility configuration, and seek the optimal layout scheme under the fairness objective. Results showed that after using the improved location-allocation models, the maximum travel time for residents was reduced from 76 ​min to 13 ​min, and the average travel time was reduced from 19 ​min to 8 ​min. Additionally, the coverage rate of the facilities increased from an average of 57% to 97%, and the spatial layout of facilities was more rational. The research results contributed to the study of spatial problems and spatial equity in facility allocation.

It is of great practical significance to identify service blind area, scientifically select park construction areas, and clarify the priority of parks' construction based on the co-ordination of supply-demand evaluation. With the urban parks within the Taiyuan Ring Expressway as the research subjects, we estimated the accessibility range and the service pressure of each park by using the application programming interface of Gaode map route planning and point of interest data to characterize their supply and demand levels. We identified the service blind areas of parks by overlay analysis, and used the location-allocation (LA) model to purposefully supply park green space. Results showed that the accessibility coverage rates of the parks by walking and bicycling within 15 minutes were 35.6% and 71.7%, respectively, indicating insufficient supply capacity of parks. The areas with large potential demand for park green space in Taiyuan were mainly concentrated in the business district of Qinxian-Changfeng Street and the Shuangta business district within Dongzhong ring road, which existed the obviously invisible blind areas. Finally, we proposed new park green space site selection proposal based on LA model. Optimization results indicated that the coverage rates of walking and bicycling within 15 minutes increased to 46.7% and 81.0%, respectively, and that the service pressure of parks was relieved. We combined the leisure demands of urban residents and the distribution of urban parks by utilizing network big data, which could promote the scientific nature and accuracy of the optimizing site selection and provide scientific method and theory basis for urban park construction. [ABSTRACT FROM AUTHOR]

The outbreak of COVID-19 poses a serious threat to global public health, and vaccination is an effective means of prevention. Studying the spatial layout and accessibility of COVID-19 vaccination sites is of great significance. The study analyzes the spatial distribution characteristics and accessibility of vaccination sites in the early stage of mass vaccination in Tianhe District, Guangzhou, based on GIS technology and combines three location allocation models: the p-median model, maximum covering location problem (MCLP) model, and location set covering problem (LSCP) model to identify candidate COVID-19 vaccination sites for the proposed public service facilities. The study found that only 47 COVID-19 vaccination sites exist in the early stage, with a small overall number, uneven spatial distribution, and trend of high accessibility in the central but low accessibility in the north and south; after the proposed addition of 31 vaccination sites, the overall distribution showed an even and dense distribution in the central and western regions, sporadic distribution in other regions, consistent with the distribution characteristics of residential communities. The areas where the accessibility of vaccination sites increased by more than 500 m accounted for 41% of the total area, and the area served by vaccination sites increased by 18%. Therefore, using the existing public service facilities to reasonably add the vaccination sites can improve the efficiency of vaccination and safeguard the establishment of a herd immunity barrier. [ABSTRACT FROM AUTHOR]

Reasonable layout of community cultural facilities is an important basis for improving residents' cultural life quality and carrying out cultural activities. In view of the insufficient combination of quantitative analysis methods with the specific situation of the community in current research, taking the agglomerated and mixed residential areas which are ubiquitous in the city and have various social and spatial problems as the research object, quantitative analysis methods such as location-allocation model are introduced and applied to the current layout analysis, cause analysis and layout optimization. Taking the Wanghailou community in Tianjin as an example, this study finds that the distribution of cultural facilities in the community is not balanced, and it is misaligned with the spatial distribution of the population. Insufficient coverage of facilities and insufficient utilization of facilities coexist, and there is a significant gap between the access to facilities and services between neighborhoods. Facility location and the adjacent isolated spatial form have important influence on the rationality of facility layout. The application of the location-allocation model combined with the appropriate adjustment of the existing spatial form can achieve twice the result with half th e effort. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, fire risk factors have increased greatly, indicating a higher requirement for urban firefighting security. Fire rescue capabilities can be effectively improved by the scientific layout of fire stations, and therefore, the optimal spatial arrangement of fire stations has practical implications for urban safety. In this paper, a method for planning the locations of urban fire stations is presented, taking into account the fire risk points of interest (POIs) data, road networks and fire station planning principles. The combined model method is validated against the nearest facility point model, and the service area model is proposed for the coverage of POIs and regional areas of planned new sites. The efficacy of the model is demonstrated through an improvement in the coverage of crosspoints of the regional area and points of interest (POIs), with increases of 10.20% and 12.43%, respectively. We applied the combined model method to Fengdong New Town, Shaanxi Province, China. A total of 11 new potential sites were proposed to improve the efficiency of spatial coverage, and subsequently, the coverage rate of the POIs and regional area reached 97.66% and 84.80%, respectively. This study provides application guidelines for the decision-making of fire services and the allocation of firefighting resources. [ABSTRACT FROM AUTHOR]

Mountain forests provide not only wood as a raw material but also numerous ecosystem services, such as protection against natural hazards, recreation and carbon sequestration, and they are important hosts for biodiversity. To manage these forests efficiently and in a target-oriented manner, both forest management planning and efficient harvesting operations are required. However, in most cases these two aspects are handled independently from each other. To link planning with forest operations, it is essential to divide forests into smaller areas with characteristics that are as homogeneous as possible, so-called forest management units (FMUs). The goal is that each FMU has self-contained fine access (e.g. skid roads, cable roads), and that the FMUs can be managed and planned independently. The aim of this study was to develop a spatial optimisation model that automatically identifies FMUs. The optimisation has three goals: [I] FMUs should be as compact as possible (spatially contiguous as the best case); [II] forest management should be technically and operationally coordinated within an FMU; and [III] FMUs should be as homogeneous as possible, for example regarding site properties, ecosystem service provided, and administrative affiliation. Results showed that our presented spatial optimisation model is a capable method for automatically identifying FMUs. The approach used to set up the model based on a p-median problem formulation (mixed integer linear programming) led to clearly comprehensible solutions that can be achieved in a reasonable computation time. Three solving strategies for successful computation implementation are described. Although the raw results must be reviewed by experts, they facilitate the planning process. More scenarios can be evaluated compared with the classical manual planning approach, ultimately leading to higher-quality solutions. • An effective method is needed to automatically identify forest management units FMUs. • FMUs have self-contained fine access and can be planned and managed independently. • A spatial optimisation model based on a p-median problem formulation was developed. • Smart solving strategies for successful computation implementation are described. • Model results facilitate the planning process, but still must be reviewed by experts. [ABSTRACT FROM AUTHOR]

Today, the number of cities implementing bike-share programs is remarkably increasing. One of the critical elements of implementing a successful bike-share program is integrating it with other transportation modes such as bus and metro and extending its coverage in high-density residential and employment areas to encourage more demand. In this study, we utilize a GIS-based method to visualize the spatial distribution of bike-share stations using the location-allocation problem, using the Capital bike-share program in Washington D.C. metropolitan areas as a study area. We chose Washington D.C. as it was one of the first cities in the United States that launched a bike-share program and currently has one of the largest bike-share systems across the country. The location-allocation problem, including Target Market Share (TMS) and Maximize Coverage and Minimize Facility (MCMF), is considered to analyze the accessibility of promoting transit modes with bike-share systems across the District of Columbia. Location-allocation models are investigated to determine the potential bike station locations accessible to the maximum population and within a 300-m buffer around public transit stations (e.g., bus, metro). The results show that the bike-share system in Washington D.C. is more accessible for transit users as an access/egress mode. At the same time, in areas farther away from downtown D.C., docking stations are more distanced apart and offer less coverage, especially in residential-only areas. Finally, our methodology can potentially be utilized for optimal station location allocation in any other city where maximum exposure is required. • Determining optimal locations of bike-share stations using GIS-based spatial approach. • Applying Target Market Share and Maximize Coverage/Minimize Facility GIS tools. • Accessibility of bike stations locations to the public transit stations and residential area. • Results confirming accessibility of bike-share system for transit users as access mode. • Results showing many residential areas have low accessibility to bike-share stations. [ABSTRACT FROM AUTHOR]

Crop residues derived from post-harvesting process have been problematic due to an on-field incineration, which caused air pollutants and greenhouse gas (GHG) emissions. An appropriate utilization of those biomasses can improve the environmental situation and provide a substitute for fossil fuels. Therefore, this study intends to analyze how left-over agricultural residues should be valorized in the decentralized bioethanol production configuration. With integrated techniques of geographical information system and multi-criteria analysis (GIS-MCA), we identify suitable locations for exhibiting decentralized sites matching the geographical backgrounds in each region. Under the precondition of a complete utilization of the agricultural residues, we found optimal installation numbers 71 units of decentralized production in total through suitability analysis. Conducting the location–allocation model, it is possible to determine production scales from the collectable spatially distributed biomass and transportation distances. Under the presumed conditions of installing 1 to 25 units, the logistics cost and total capital investment can reach USD 1.17–2.46 L−1 and USD 1.17–6.93 L−1, respectively. The results from examining the technical potential and economic feasibility aspects are key to designing decentralized bioethanol production facilities and maximizing the utilization of agricultural residues in Thailand. [ABSTRACT FROM AUTHOR]

• We propose an innovative methodology for optimal deployment of public EV chargers. • A generalised ordered probit model is used to estimate EV purchase intention. • We derive parameters of the LA model based on survey, public data and interview. • Existing charging network should be substantially expanded, especially in suburbs. • Adding chargers at existing stations is more economical than building new stations. The optimal deployment of public charging infrastructure is critical to the popularisation of electric vehicles (EVs) in high-density cities. Existing studies on public EV charging facilities have rarely integrated government policy and spatial constraints into their optimisation algorithms. To address this research gap, we proposed a contextualised EV charger optimisation model that incorporates carefully derived supply-and-demand constraints and tested it in the case of Hong Kong. From the supply side, we studied the latest planning guidelines and conducted a spatial analysis of potential charging sites. From the demand side, we conducted a questionnaire survey with local residents, estimated their EV purchase intention using a generalised ordered probit model, and then projected the usage demand for public chargers. These supply-and-demand constraints were subsequently incorporated into a location-allocation model to minimise both charging demand shortfall and travel time to charging facilities. We also conducted sensitivity analyses with varying budget, charging demand and facility service radius. Based on our results, we made several key recommendations regarding the spatial planning of public EV charging facilities in our high-density context: (1) the existing charging network should be substantially expanded to meet the projected demand; (2) the charging network should be expanded beyond the central business district and the urban core into other urban neighbourhoods and suburbs; and (3) installing more chargers at existing charging stations is more economical than building new stations. Our research provides an important reference for the spatial planning and deployment strategies for public EV charging infrastructure in high-density cities. [ABSTRACT FROM AUTHOR]

With the rapid development of urbanization, fire risk factors have increased greatly, indicating a higher requirement for urban firefighting security. Fire rescue capabilities can be effectively improved by the scientific layout of fire stations, and therefore, the optimal spatial arrangement of fire stations has practical implications for urban safety. In this paper, a method for planning the locations of urban fire stations is presented, taking into account the fire risk points of interest (POIs) data, road networks and fire station planning principles. The combined model method is validated against the nearest facility point model, and the service area model is proposed for the coverage of POIs and regional areas of planned new sites. The efficacy of the model is demonstrated through an improvement in the coverage of crosspoints of the regional area and points of interest (POIs), with increases of 10.20% and 12.43%, respectively. We applied the combined model method to Fengdong New Town, Shaanxi Province, China. A total of 11 new potential sites were proposed to improve the efficiency of spatial coverage, and subsequently, the coverage rate of the POIs and regional area reached 97.66% and 84.80%, respectively. This study provides application guidelines for the decision-making of fire services and the allocation of firefighting resources.

The objective of this study was to develop a new method for freight movement in urban areas by combining a light rail transit system and a road transport system to distribute and deliver parcels. Utilisation of light rail transportation systems for parcel delivery can help reduce traffic congestion and air pollution in cities. This paper presents a location–allocation model to determine the optimum number and location of light rail stations suitable to establish rail distribution hubs, in a bid to minimise transportation costs. A case study is conducted to assess this approach in the city of Bangkok. The results show that the cost, time, and distance of transportation can be reduced by 10%, 16.67%, and 33.33%, respectively.

The objective of this study was to develop a new method for freight movement in urban areas by combining a light rail transit system and a road transport system to distribute and deliver parcels. Utilisation of light rail transportation systems for parcel delivery can help reduce traffic congestion and air pollution in cities. This paper presents a location–allocation model to determine the optimum number and location of light rail stations suitable to establish rail distribution hubs, in a bid to minimise transportation costs. A case study is conducted to assess this approach in the city of Bangkok. The results show that the cost, time, and distance of transportation can be reduced by 10%, 16.67%, and 33.33%, respectively. [ABSTRACT FROM AUTHOR]

Purpose - The purpose of this paper is to study the optimization of the geographical location of a network of points of sale, so that each retailer can have access to a potential geographic market. In addition, the authors study the importance of the distance variable in the commercial viability of a point of sale and a network of points of sale, analysing if the best location for each point (local optimum) is always the best location for the whole (global optimum). Design/methodology/approach - Location-allocation models are applied using p-median algorithms and spatial competition maximization to analyse the actual journeys of 64,740 car buyers in 1240 postal codes using a geographic information system (GIS) and geomarketing techniques. Findings - The models show that the pursuit of individual objectives by each concessionaire over the collective provides poorer results for the whole network of points of sale when compared to coordinated competition. The solutions provided by the models considering geographic and marketing criteria permit a reduction in the length of journeys made by the buyers. GIS allows the optimal control of market demand coverage through the collaborative strategies of the supplying retailers, in this case, car dealerships. Originality/value - The paper contributes to the joint research of geography and marketing from a theoretical and practical point of view. The main contribution is the use of information on actual buyer journeys for the optimal location of a network of points of sale. This research also contributes to the analysis of the correlation between the optimum local and optimum global locations of a commercial network and is a pioneering work in the application of these models to the automotive sector in the territorial area of the study.

In this paper, we address a decision-making problem related to the requirement of costly equipment by medical diagnostic services in a segmented public healthcare system comprising several institutions and private providers. The problem is motivated by a real-world case of the Mexican healthcare system. The aim of this study is to determine which hospitals can provide the service, their capacity levels, the allocation of demand in each institution, and the referral of patients to other institutions or private providers while minimizing annual investment costs and operating costs required to satisfy demand. A mixed-integer linear programming model that takes into account different characteristics such as patient acuity levels, types of equipment, and demand variation through time is introduced. The model was empirically assessed to evaluate its impact on the decision-making process. A sensitivity analysis to evaluate solution behavior for variations of critical parameters was performed. The results showed that some values could generate a significant effect on the total costs for the service coverage and in the efficiency of the service, whereas overall results indicated the usefulness of the model. While this model is valuable to aid this decision-making problem, it is limited to medium-size instances of up to 90 facilities. To solve the problems with larger instances, a two-phase heuristic algorithm is proposed. In the first phase, the method uses a greedy construction mechanism, and in the second phase, it attempts to improve the solution. Empirical evidence on large instances shows that good solutions with low computing times are reached in comparison with the exact method. [ABSTRACT FROM AUTHOR]

Highlights • An uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation model is proposed. • Two meta-heuristic method and one exact method are provided to solve the model. • Several types of injured people are considered in earthquake evacuation planning. • Failure rate of the centers are modeled using reliability and probability concepts. • The proposed model has been applied in a real case study in Tehran, Iran. Abstract In this paper, an uncertain multi-objective multi-commodity multi-period multi-vehicle location-allocation mixed-integer mathematical programing model is proposed for the response phase of the earthquake. The proposed model includes five echelons as affected areas, distribution centers, hospitals, temporary accommodation centers and temporary care centers. Two objective functions as minimizing the total cost of the location-allocation of facilities and minimizing the amount of the shortage of relief supplies, are considered. The uncertainty is modeled using a scenario-based probability approach. The main decisions made by the proposed model are locating of the temporary care and accommodation centers, allocation of the affected areas to the located centers and hospitals, as well as the allocation of the distribution centers to temporary accommodation centers. Several decisions associated with flow of injured people and commodities between facilities, and decisions associated with number of vehicles between facilities and shortage and inventory level at centers are also made by the proposed model. Several sets of constraints including demand and flow of relief commodities, capacity of centers, transportation of injured people, capacity of transportation vehicles for commodities and injured people, and back up centers are considered in multiple periods of planning in the proposed model. The proposed model is applied in a real case study in Tehran. The model is solved using modified multiple-objective particle swarm optimization (MMOPSO), Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and epsilon constraint method. The performance of the solution procedures is analyzed using multi-objective performance evaluation metrics. The results reveal the superiority of the MMOPSO over the other solution approaches. A preferred solution, from the set of non-dominated solutions generated by MMOPSO, has been selected, analyzed and described. Sensitivity analysis on main parameters of proposed model and the probabilities of the earthquake and failures of the facilities has also been accomplished. [ABSTRACT FROM AUTHOR]

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance.

There has been considerable interest in the development of analysis techniques for Geographical Information Systems (GIS). This includes such normative spatial models as vehicle routing models, districting and turfing models for dividing up land into territories for schools, sales/service, and voting, and location models for identifying sites or patterns of sites to provide service accessibility. The GIS system may provide a unique data base for application and analysis. This paper discusses several problems associated with the integration of a normative location model into a GIS. A number of specifics associated with the p-median model are given. These include: demand zone definition, facility site definition, and solution algorithm selection and development. Within the context of selecting a solution process, we show that such a selection is not necessarily an easy one to make. We demonstrate that the best such solution technique may have some potential drawbacks in application. We present the results of several test applications and a glimpse of the pathology of the final solutions. This discussion raises a major, but often ignored, issue involving the application of a location heuristic: namely, how often should we restart a heuristic to help ensure that the best solution found is optimal or near-optimal. We propose and test a dynamic stopping rule that can be used to help ensure that the best solution is identified. The results of this analysis can be of great, practical value in the successful application of location models within a GIS framework.

Emergency medical services (EMS) systems provide out-of-hospital acute medical care and transportation to the appropriate health care provider to patients with illnesses and injuries. The objective of EMS systems is to satisfy demand requests by providing timely first care medical assistance to patients at the incident scene. This paper aims at designing a robust two-tiered EMS system while accounting for the inherent uncertainty of the demand. A two-stage stochastic programming location-allocation model is proposed to simultaneously determine the location of ambulance stations, the number and the type of ambulances to be deployed, and the demand areas served by each station. This problem is then solved efficiently using the sampling average approximation algorithm. Computational experiments highlight the performance of the proposed solution approach and its practical applicability. [ABSTRACT FROM AUTHOR]

Substantial motor vehicle exhaust, a primary cause of air pollution, is emitted on short car trips of three miles or less. Bicycles have been considered an optimum means of completing these short trips because the bicycle is an environmentally friendly, economical, and convenient vehicle. Accordingly, many countries have adopted public bicycle-sharing systems to reduce the use of private vehicles for short trips in central downtown areas. In this paper, we propose a new framework, based on taxi trajectory data, for locating bicycle-sharing stations most efficiently to replace short automobile trips. The proposed framework is applied to Gangnam- gu , a district within the city of Seoul, Korea. Results using two different location-allocation models are demonstrated. As expected, when the p-median model was implemented, the selected stations were more scattered over the whole district, whereas when the MCLP model was implemented, the stations were more concentrated on central areas. Our approach is applicable to any city considering a bicycle-sharing system and can contribute to the system’s efficiency in improving environmental conditions in a central downtown area. [ABSTRACT FROM AUTHOR]

In recent years, extreme natural hazards threaten cities more than ever due to contemporary society's high vulnerability in cities. Hence, local governments need to implement risk mitigation and disaster operation management to enhance disaster resilience in cities. Transforming existing open spaces within cities into emergency shelters is an effective method of providing essential life support and an agent of recovery in the wake of disasters. Emergency shelters planning must identify suitable locations for shelters and reasonably allocate evacuees to those shelters. In this paper, we first consider both the buildings' post-disaster condition and the human choice factor that affect evacuees' decision, and propose a forecasting method to estimate the time-varying shelter demand. Then we formulate an integrated location-allocation model that is used sequentially: an emergency shelter location model to satisfy the time-varying shelter demand in a given urban area with a goal of minimizing the total setup cost of locating the shelters and an allocation model that allocates the evacuees to shelters with a goal of minimizing their total evacuation distance. We also develop an efficient algorithm to solve the model. Finally, we propose an emergency shelters planning based on a case study of Shanghai, China. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the efficiency and equity of the existing civil defense centers locations in Amman city and to evaluate their distribution regarding to population, buildings, and accidents densities within the study area. In addition, GIS-based Location-Allocation Model and Network Analysis methods were used to define the optimal locations for new suggested civil defense centers to fit with the number of population, buildings and accidents in the city in order to improve the efficiency and equity of these centers. The study results showed differences in the importance of the civil defense centers based on the number of population, buildings and the number of accidents. Thus, the civil defense centers were classified into three categories (centers with high, medium or low importance) based on the importance of their locations for the number of population and buildings served as well as the number of accidents using the Ordinal Scale method. The results have also showed that only 139 out of 205 neighborhoods are covered and served by the existing civil defense centers using the proposed time of 7 minutes coverage. Therefore, the study suggested six new civil defense centers to be established in order to raise the number of served neighborhoods to 180 using the GIS-based Location-Allocation Model. [ABSTRACT FROM AUTHOR]

Disasters, occurring more frequently and severely, have had significant effects on the elderly, who are particularly vulnerable. In response to this risk, there has been increased focus on the emergency shelter planning. This study investigates the location-allocation of fixed shelters for the elderly, considering their needs for evacuation and refuge. A multi-objective model for the location-allocation of fixed shelters is developed, and is solved using genetic algorithms and simulated annealing algorithms. Then, the model is used to compare the location-allocation of fixed shelters in two scenarios: when there are no differences in the needs of the elderly and non-elderly refugees for evacuation and refuge, and when there are differences in their needs. This study also analyzes the current situation of the elderly population and fixed shelters in four urban districts of Hefei, and selects Luyang district, where there is a high demand of the elderly for refuge compared to the supply of fixed shelters, as a case study. Results show that when considering the needs of the elderly, the success rate of evacuation and refuge in Luyang district is decreased by 1.88%, with the elderly refugees who can evacuate independently having the lowest success rate, 87.36%, among all refugees. Empirical tests also reveal that the optimization of fixed shelters for the elderly can be achieved by utilizing public buildings to increase the number of fixed shelters, and by building indoor refuge rooms for the elderly refugees in outdoor fixed shelters to improve the type structure of the fixed shelters. [ABSTRACT FROM AUTHOR]

It is of great practical significance to identify service blind area, scientifically select park construction areas, and clarify the priority of parks' construction based on the co-ordination of supply-demand evaluation. With the urban parks within the Taiyuan Ring Expressway as the research subjects, we estimated the accessibility range and the service pressure of each park by using the application programming interface of Gaode map route planning and point of interest data to characterize their supply and demand levels. We identified the service blind areas of parks by overlay analysis, and used the location-allocation (LA) model to purposefully supply park green space. Results showed that the accessibility coverage rates of the parks by walking and bicycling within 15 minutes were 35.6% and 71.7%, respectively, indicating insufficient supply capacity of parks. The areas with large potential demand for park green space in Taiyuan were mainly concentrated in the business district of Qinxian-Changfeng Street and the Shuangta business district within Dongzhong ring road, which existed the obviously invisible blind areas. Finally, we proposed new park green space site selection proposal based on LA model. Optimization results indicated that the coverage rates of walking and bicycling within 15 minutes increased to 46.7% and 81.0%, respectively, and that the service pressure of parks was relieved. We combined the leisure demands of urban residents and the distribution of urban parks by utilizing network big data, which could promote the scientific nature and accuracy of the optimizing site selection and provide scientific method and theory basis for urban park construction.

In Surakarta and its surroundings (Solo Raya), there exists more than 400 Small-Medium Enterprises (SMEs) that produce finished products of rattan. Due to the high procurement cost as total operational cost of raw rattan distribution network from the sources, e.g. Borneo and Celebes to the rattan industries, the competitiveness of their products is lower than products from other countries. Therefore, to overcome the problem, those costs should be reduced for example by aggregating the demand of rattan industries. This police needs to be supported by the warehouse for storing and distributing raw rattan. Hence, this research aims to develop a facility location-allocation model so that total supply chain costs, including raw rattan procurement costs as well as facilities opening and closing costs can be minimized. The location-allocation model will be presented in a mixed integer non-linear programming model and solved using MS-Excel Solver. The results are number and location of the warehouse along with the raw rattan allocation in the warehouse to ensure raw rattan supply for rattan industries.

Envisioning a sustainable biorefinery requires reliable information on the sustainable availability of biomass, optimal plant location and delivered cost. In this paper, we have developed an integrated Geographic Information System (GIS) based sustainable biomass assessment, site optimization and supply logistics cost model to assess the spatial and temporal availability of crop residues, to identify optimal plant sites and to calculate the delivered cost. The grid-level (30 × 30 m) assessment model was developed for crop residues using three primary sustainability indicators: (1) Soil Erosion (SE), (2) Soil Conditioning Index (SCI) and (3) Crop residue yield ⩾2.5 dry Mg/ha. The Artificial Neural Networks (ANNs) prediction models for each indicator were developed and implemented in the GIS platform to assess sustainably available crop residues. A multi-criteria geospatial analysis was used to identify suitable plant sites. GIS-based location-allocation model was used to site biorefineries/plants at optimal locations and generate feedstock supply curves. The developed model was demonstrated with the sustainable assessment of cotton stalk (CS) to produce fuel pellets in the study region (Georgia, USA). The model has estimated that about 1.6 million dry Mg of CS is available annually to support seven pellet plants with an average annual plant capacity of 200,000 dry Mg. The average delivered cost of CS ranged between 68 and 75 $/dry Mg delivered as large rectangular bales with the transport radii ranged from 31 to 60 km. The spatial and temporal variations in the topology and crop yield directly influenced the sustainable availability of CS, the optimal plant location and its capacity and the delivered cost. However, the changes in the optimal plant location and delivered cost were minimal for large capacity plants (>400,000 dry Mg). The developed model can be used to assess multiple crop residues, to manage and control feedstock supply risks and delivered cost variations for a sustainable biorefinery. [ABSTRACT FROM AUTHOR]

Trauma is considered a "modern civilized sickness", and its occurrence substantially affects all of society, as well as individuals. The implementation of trauma emergency systems in cities with young, prosperous, and highly mobile populations is necessary and significant. A complete trauma emergency system includes both low-level trauma centers that offer basic emergency services and high-level trauma centers that offer comprehensive services. GIS and operational research methods were used to solve the location problem associated with these centers. This study analyzed the spatial distribution characteristics of trauma demands and the candidate locations of trauma centers based on a spatial analysis and presented a hierarchical location-allocation model for low- and high-level trauma centers in Shenzhen. The response, coverage, treatment and cost capacities of the trauma center locations were considered, and an ant colony optimization was used to calculate the optimal solution. The objectives of this study were to optimize trauma center locations, improve the allocation of medical trauma resources and reduce the rate of deaths and disabilities due to trauma. [ABSTRACT FROM AUTHOR]

The development of mathematical and optimization models for reverse supply network design has concerned considerable interest over the past decades. However, the uncertainties that are inherent in the network design and the complex interactions among various uncertain parameters are challenging the capabilities of these developed tools. The aim of this paper is to propose a new mathematical programming model for recycling network design in the iron and steel industry. The considered recycling network is multi-echelon, multi-facility, multi-product, and multi-supplier. Moreover, another objective of this research is to introduce an interval-stochastic robust optimization methodology to deal with various uncertainties in the proposed model. Computational experiments are provided to demonstrate the applicability of the proposed model in recycling network design. [ABSTRACT FROM AUTHOR]

Abstract: The concept of “networking” has become central to the reform of healthcare systems. The objective is to reduce costs while improving the quality of service. This paper deals with the problem of sterilization service configuration within a hospital network. Two alternatives are considered: (1) each hospital in the network maintains its sterilization service in-house; (2) a central sterilization service ensures this function for all hospitals in the network. This decision is based on a location–allocation model of the sterilization service. A Mixed Integer Linear Program (MILP) is proposed to find the optimal configuration of the sterilization service (centralized vs. distributed), the optimal location and the optimal capacity of the centralized sterilization service over a multi-period planning horizon. The objective is to minimize costs related to transportation, production and resource acquisition and transfer. A solution method based on the addition of appropriate customized cuts to the original MILP is then proposed. The proposed models are applied to 30 scenarios extracted from a real-life case study. The obtained results show that the considered problem can be solved to optimality for moderate size scenarios with the use of commercial MILP solvers and the addition of the proposed customized cuts to the original model. Further analysis was conducted and pointed out how network configuration is sensitive to the number of human and material resources available in each hospital of the network. [Copyright &y& Elsevier]

The location problem considered in this paper concerns the optimal number, size, and location of public logistic centers. To solve this problem, a mathematical model is developed based on an expanded capacity-limited fixed cost location-allocation model of a network incorporating handling costs and the costs of the temporary storage of cargo in the logistic center. The effectiveness of the proposed approach is evaluated with a numerical example of locating public logistic centers of international importance in the Republic of Serbia, based on two scenarios regarding the future development of import cargo flows into the Republic to the year 2020. [ABSTRACT FROM AUTHOR]

Nowadays, in the competitive market, commercial companies due to their economic problems and also restrictions imposed by international organizations to comply with environmental regulations are making noticeable efforts to reduce the level of their wastes in their manufacturing systems and consequently the level of waste in consumers' products. In harmony with this issue, one of the most effective ways which has successfully been used and proven to be economically profitable is to take products lifecycles into consideration. Consideration of products lifecycle has made supply chain practitioners to investigate the reverse logistics activities in addition to forward logistics activities. Hence, corporations, in order to reduce their cost on the one hand and boosting their efficiency on the other hand, were obligated to employ closed loop supply chain models to concurrently benefit from its economical and environmental advantages. Therefore, in this paper, a mixed nonlinear facility location-allocation model is proposed for recycling collection centers. The considered closed loop logistics model consists of multiple echelons, multiple suppliers, multiple collection centers, multiple time period and also multiple facilities. In real-life problems parameters like demand, cost, capacity, distances, and quantities of returned products are always uncertain. Therefore, in order to solve a realistic problem, foregoing parameters are considered as fuzzy in our proposed model. Subsequently, to solve fuzzy mixed nonlinear programming model, one of the most effective technique in the literature is used. Additionally, in order to demonstrate the behavior of the parameters employed in the model, a comprehensive sensitivity analysis is conducted. Computational results demonstrate that the proposed model can show favorable efficiency in solving supply chain problems. [ABSTRACT FROM AUTHOR]

Abstract: Northern Ohio supports a small population of greater sandhill cranes (Grus canadensis tabida) that is currently listed as state-endangered. Population restoration efforts are currently under consideration, although it is not known if habitats in the state can support additional nesting pairs. Accurate estimates of breeding pair carrying capacity are necessary before conservation efforts can be effectively developed and implemented. We estimated carrying capacity for nesting sandhill cranes using habitat suitability and spatial optimization models. We first developed a spatially explicit habitat suitability index (HSI) model to identify suitable nesting sites at five locations in northern Ohio. We then used the HSI output to estimate the carrying capacity at each location. We modeled carrying capacity as an anti-covering location problem, a spatial optimization model that determines the maximum number of breeding pairs an area can support, given that nests must be spaced 3000m apart. Our results indicate that habitats in Ohio where cranes currently breed are near carrying capacity, while unoccupied suitable habitats are available in other portions of the state. This analysis enables wildlife managers to identify priority locations for crane conservation in Ohio and to determine which restoration efforts (e.g. habitat restoration or population augmentation) are most likely to succeed at each location. Our methodology provides an important and innovative conservation tool that can be applied to other species with strong attachment to sites (e.g. nest or den) that are optimally spaced at some minimum distance from conspecifics, competitors, predators, or sources of disturbance. [Copyright &y& Elsevier]

In developing countries, including India, the role of the private sector in the provision of basic healthcare services is gradually expanding, since the public sector provides limited services and covers only limited areas. Using location-allocation models (LAM), this paper (1) examines the changing geographic access to and locational efficiency of basic public healthcare vis-a`-vis private healthcare services in two districts located in northwestern part of India, and (2) interrogates the factors that govern their geographic accessibility and locational-efficiency.Although this research confirms regional inequalities in geographic accessibility and locational efficiency of both public and private healthcare services in the selected districts, the locational efficiency of private health services is significantly lower than that of public health services. This paper further demonstrates the use of LAM for new site identification (keeping the existing healthcare sites intact) that will, in the future, improve locational efficiency of these services. This paper not only recommends improved geographic access to both public and private health services and their enhanced complementary role, but also stresses the need to evaluate geographic access from the service-users’ perspective and the use of more realistic data on demand and supply in future research. The findings of this paper can be extended to areas with similar geographic settings, and socio-economic and demographic conditions. [Copyright &y& Elsevier]

In the 1990s, and even more since the Bosman Case, professional football in Europe has been transformed from a utility maximisation to a more endogenous growth-based profit maximisation consumer-oriented service. In the post-Bosman period Belgian football has declined in the European rankings and has in a more economic-oriented climate problems in surviving. The recent transformation implies that in the long run the economic features and more specific the location of the club is becoming a very important factor. The existing heterogeneous characteristics of the different clubs made it necessary to introduce an empirically-based modified maximum covering location model. The empirical results prove that a restructuring of Belgian professional football to 14 clubs and in some cases a relocation or merger might be a solution for the contemporary problems. [ABSTRACT FROM AUTHOR]

This work developed models to identify optimal spatial distribution of emergency evacuation centers (EECs) such as schools, colleges, hospitals, and fire stations to improve flood emergency planning in the Sylhet region of northeastern Bangladesh. The use of location-allocation models (LAMs) for evacuation in regard to flood victims is essential to minimize disaster risk. In the first step, flood susceptibility maps were developed using machine learning models (MLMs), including: Levenberg–Marquardt back propagation (LM-BP) neural network and decision trees (DT) and multi-criteria decision making (MCDM) method. Performance of the MLMs and MCDM techniques were assessed considering the area under the receiver operating characteristic (AUROC) curve. Mathematical approaches in a geographic information system (GIS) for four well-known LAM problems affecting emergency rescue time are proposed: maximal covering location problem (MCLP), the maximize attendance (MA), p-median problem (PMP), and the location set covering problem (LSCP). The results showed that existing EECs were not optimally distributed, and that some areas were not adequately served by EECs (i.e., not all demand points could be reached within a 60-min travel time). We concluded that the proposed models can be used to improve planning of the distribution of EECs, and that application of the models could contribute to reducing human casualties, property losses, and improve emergency operation. [Display omitted] • Flood susceptibility models are proposed using machine learning and MCDM. • Model validation show that LM-BP model was more reliable than DT and ESWARA models. • Location-allocation models (PMP, LSCP, MCLP, MA) were used for evacuation planning. • The proposed methods can be used to improve flood emergency planning. [ABSTRACT FROM AUTHOR]

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance. [ABSTRACT FROM AUTHOR]