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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]

• 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]

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]

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]

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]

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]

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]

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]

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]

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]