Candidate Locations Research Articles

Multi-Performance Estimation for Deploying Bank Branches Based on a Multi-Task Attentive Tree-Enhanced Model

Selecting the optimal location for a new bank branch is challenging but worth studying due to its importance to growing a successful business. Bankers have been devoting a lot of effort to this issue. In recent years, the proliferation of multisource data in smart cities has called for more need for data-driven optimal location selection. Previous studies usually focus on mining different features and processing these data through domain expert knowledge. However, they fail to discover potential complicated factors interactions. Besides, most of these studies only use a single indicator to evaluate the candidate locations, which overlooks a lot of information, resulting in an inaccurate evaluation. In this study, we propose MATE, a Multi-task Attentive Tree-Enhanced model, to simultaneously predict multiple performance indicators of a bank branch's location. Our model takes advantage of the tree-based model, which can effectively extract cross features and provide interpretability according to inferred decision rules. In addition, we designed the financial embedding module and attentive interaction blocks, allowing MATE to obtain more complex and diverse features. Finally, extensive experiments on real-world bank datasets demonstrate the effectiveness of our method, which outperforms baseline and state-of-art methods from 17% to 41%.

A study on optimization of delayed production mode of iron and steel enterprises based on data mining.

Delayed production mode has been adopted by an increasing number of process production enterprises as a method to realize mass customization of multi-products. This paper used the convolutional neural network-long short-term memory artificial neural network algorithm (C-LSTM) in data mining technology to analyze and determine factors that have an impact on delayed production mode in the internal and external production and operation of enterprises. Combined with the actual production situation of iron and steel enterprises, a quantitative model of the delayed production was constructed. Lastly, data from a large iron and steel enterprise with good operation was used to verify the validity of the proposed model and analyze key influencing factors. According to the research, in scenarios of considering PDP alone, considering CODP alone, considering both PDP and CODP, considering PDP and CODP and using data mining technology to model, the matching degree of these methods with the actual situation of the enterprise is 31.8%, 61.4%, 71.6% and 86.6%, respectively. The numerical analysis results of the model based on data mining technology show that in delayed production, when customer service level improves or the delay penalty coefficient increases, the optimal locations of the product differentiation point (PDP) and customer order decoupling point (CODP) move toward the end of production, and the total cost increases gradually. When the difference in production cost or benefit of early delivery between the candidate locations of PDP and CODP is small, optimal locations of PDP and CODP are close to the beginning of the general and dedicated production processes. With an increase of cost difference or early delivery benefit, the optimal locations of PDP and CODP jumped to the end stage of the general and dedicated production processes, and the total cost begins to decrease.

Hub and Distribution Center Location for a Third-Party Logistics service Provider: A Case Study at Tehran

The rapid growth of the transportation industry and the advance of the e-commerce have opened opportunities for boom delivery services companies. Although, intense competition between shipping companies has obliged many to amend their shipment networks. In this setting, we aim to provide high-quality shipping services for a third-party logistics company in Iran. Currently, in the selected company, one hub is in the west part of Tehran that gives services to all customers. There are some difficulties in shipping services to the eastern part of Tehran city. Therefore, in this paper, we find the location of another hub center to streamline the shipping process. Moreover, to promote our service levels, some Distribution Centers (DCs) are going to be set up. Due to the lack of shipment data like pick up and delivery data, we tried to find the locations of the hub and the DCs based on Tehran population's data. We clustered 122 regions of Tehran based on population, economic index, accessibility to the internet, and the number of business units. Since some remote regions (which are not in the same vicinity) belong to the same cluster, we defined a relative distance criterion to avoid making remote regions in the same cluster. In each cluster, a fixed or movable DC can be set up to service the regions of its cluster. Moreover, to find the best candidate locations for the hub, each zone of Tehran was assessed based on some criteria like land cost, accessibility to the highways, and distance to its nearest bus terminal. Based on these criteria, some zones have been dominated by others, and the remains were considered as candidate locations in a hub location model. By considering the DCs as spokes in a hub and spoke model, the optimal location for the eastern hub establishment was determined.

Developing a Decision-Making Process of Location Selection for Truck Public Parking Lots in Korea

As the number of truck registrations and the traffic volume have increased continuously in urban areas, the problem of truck illegal parking on the roadside has become more serious in Korea. Although the government presented the necessity and the construction plan of the truck public parking lots through the ‘4th Comprehensive Plan for Expansion of Truck Resting Facilities’, there is no detailed guideline for the local government of where to construct them. The previous studies on the location selection of the parking lots have mainly focused on passenger cars and buses, but not trucks, and the process for candidate location selection was not mentioned. To fill this gap, this study presents a decision-making process for the location selection of truck public parking lots in urban areas based on mixed-integer programming; it includes a candidate location selection by spatial analysis and an optimal location determination by the application of the competitive p-median algorithm. A case study of Incheon was conducted to validate the presented decision-making process. This study introduced a systematic decision-making process that includes standards establishment, data processing, and methodology application; it is universalistic enough to be utilized as a guideline for the government to efficiently construct truck public parking lots.

Widespread habitat for Europe's largest herbivores, but poor connectivity limits recolonization

AbstractAimSeveral large‐mammal species in Europe have recovered and recolonized parts of their historical ranges. Knowing where suitable habitat exists, and thus where range expansions are possible, is important for proactively promoting coexistence between people and large mammals in shared landscapes. We aimed to assess the opportunities and limitations for range expansions of Europe's two largest herbivores, the European bison (Bison bonasus) and moose (Alces alces).LocationCentral Europe.MethodsWe used large occurrence datasets from multiple populations and species distribution models to map environmentally suitable habitats for European bison and moose across Central Europe, and to assess human pressure inside the potential habitat. We then used circuit theory modeling to identify potential recolonization corridors.ResultsWe found widespread suitable habitats for both European bison (>120,000 km2) and moose (>244,000 km2), suggesting substantial potential for range expansions. However, much habitat was associated with high human pressure (37% and 43% for European bison and moose, respectively), particularly in the west of Central Europe. We identified a strong east–west gradient of decreasing connectivity, with major barriers likely limiting natural recolonization in many areas.Main conclusionsWe identify major potential for restoring large herbivores and their functional roles in Europe's landscapes. However, we also highlight considerable challenges for conservation planning and wildlife management, including areas where recolonization likely leads to human–wildlife conflict and where barriers to movement prevent natural range expansion. Conservation measures restoring broad‐scale connectivity are needed in order to allow European bison and moose to recolonize their historical ranges. Finally, our analyses and maps indicate suitable but isolated habitat patches that are unlikely to be colonized but are candidate locations for reintroductions to establish reservoir populations. More generally, our work emphasizes that transboundary cooperation is needed for restoring large herbivores and their ecological roles, and to foster coexistence with people in Europe's landscapes.

Continuous covering on networks: Improved mixed integer programming formulations

Covering problems are well-studied in the domain of Operations Research, and, more specifically, in Location Science. When the location space is a network, the most frequent assumption is to consider the candidate facility locations, the points to be covered, or both, to be finite sets. In this work, we study the set-covering location problem when both candidate locations and demand points are continuous on a network. This variant has received little attention, and the scarce existing approaches have focused on particular cases, such as tree networks and integer covering radius. Here we study the general problem and present a Mixed Integer Linear Programming formulation (MILP) for networks with edge lengths no greater than the covering radius. The model does not lose generality, as any edge not satisfying this condition can be partitioned into subedges of appropriate lengths without changing the problem. We propose a preprocessing algorithm to reduce the size of the MILP, and devise tight big-M constants and valid inequalities to strengthen our formulations. Moreover, a second MILP is proposed, which admits edge lengths greater than the covering radius. As opposed to existing formulations of the problem (including the first MILP proposed herein), the number of variables and constraints of this second model does not depend on the lengths of the network’s edges. This second model represents a scalable approach that particularly suits real-world networks, whose edges are usually greater than the covering radius. Our computational experiments show the strengths and limitations of our exact approach to both real-world and random networks. Our formulations are also tested against an existing exact method.

A strategy for sustainable urban water management using water network partitioning with optimal booster pump configuration: A case study

The functionality of water distribution networks (WDNs) plays an important role in preserving human welfare and the sustainable development of cities and society. Like administrative units in urban governance models, a large-scale WDN is partitioned into district metered areas (DMAs) to improve operation and management efficiency. Conventional approaches for water network partitioning (WNP) into DMAs mainly focus on the determination of DMA sizes and configurations (i.e., the clustering phase). They subsequently form a set of boundary pipes to optimally locate flowmeters and gate valves (i.e., the sectorization phase) aimed at minimizing costs and water leakage and improving network reliability. Alternatively, this paper presents a new approach that considers the phasing of the optimal booster pump installation combined with the design of a DMA configuration aimed at optimizing the operation cost and hydraulic performance. The proposed method combines the overall sectorization process to simultaneously optimize the locations of the flowmeters, gate valves, and booster pumps, as well as the pump sizes. The proposed method was applied to a real-world WDN and the results showed two advantages: first, the boundary pipes are good candidate locations for booster pump installation, which makes it possible to improve hydraulic performance; and second, operation costs are reduced when compared to those of the source-connecting central pump configuration. This study provides a methodology to select the most suitable pumping configurations for DMA design/operation in WDNs.

DETA: A Point-Based Tracker With Deformable Transformer and Task-Aligned Learning

Current point-based trackers are usually implemented by the following two branches: a classification branch for predicting the target candidate locations and a regression branch for regressing the tracking box, which may lead to a spatial misalignment between the two tasks. Meanwhile, they ignore a meaningful exploration on how to define positive and negative samples during training and explicit border information for accurate box prediction. In this research, we investigate the key issues of point-based trackers and unlock their key limitations. First, we design a novel task-aligned component and a new loss function, named task-aligned loss, to learn the alignment of the classification and regression tasks. Second, we introduce a border alignment (BorderAlign) component in both the classification and regression branches to effectively exploit the border features of a tracking target. Third, we develop an adaptive training sample assignment (ATSA) to adaptively divide the positive and negative samples based on the statistical characteristics of the tracking object. Finally, a deformable transformer is developed to enhance the representations of search features and explore rich temporal contexts among video frames. Extensive experimental results demonstrate that the proposed tracker achieves state-of-the-art performance on six tracking benchmark datasets.

Sistem Penentuan Lokasi Menara Base Transceiver Station dengan Algoritma AHP-TOPSIS

Cellular telecommunication technology has now become an inseparable part of the increasingly mobile pattern of human life, this of course has an impact on the number of uses of cellular telecommunication technology which is increasing every day. This increase has encouraged cellular telecommunications technology vendors to continuously improve the quantity and quality of their telecommunications networks by establishing telecommunications equipment such as Base Transceiver Station (BTS) towers at strategic points. This study aims to build a system for determining the location of BTS towers that can provide visualization of information on the distribution of existing BTS towers and their coverage area radius. Analysis and location determination using a combination of AHP and TOPSIS methods. The AHP method is used to determine the objectivity of the weight and importance of the BTS tower location criteria. Furthermore, the results of the comparison of criteria will be used in the TOPSIS method to assess the rating of each candidate location. The results of the study obtained that the criteria for the location of BTS towers were population density with a weight of 0.42, the distance of the existing tower was 0.2, location access was 0.31, and the installation cost was 0.08. Meanwhile, the candidate locations were measured using linguistic variables with a weight of 0.67 for very good criteria, 0.23 for good, and 0.10 for good enough. System testing was carried out on determining the location of the BTS tower in Sinjai Borong District by analyzing three candidate locations and the results obtained that the Samaenre location was the best candidate with a rating value of 0.74.

Urban Expansion Simulation Coupled with Residential Location Selection and Land Acquisition Bargaining: A Case Study of Wuhan Urban Development Zone, Central China’s Hubei Province

The urban expansion process involves multiple stakeholders whose interactions and decision-making behaviors have a complex impact on urban land conversion. In this study, we established an urban expansion simulation model that couples two sub-models: the residential location selection model and the land acquisition bargaining model. Those sub-models include four types of agents: resident agent (RA), real estate developer agent (DA), government agent (GA), and farmer agent (FA). The residential location selection model is composed of three agents, RA, DA, and GA, and is first used to select residential locations, while an artificial neural network (ANN) is used to define the behavior rules of RA and RA selects pixels as candidate locations according to the joint decision probability. Then the land acquisition bargaining model is used, which is composed of GA and FA. If the land acquisition is successful, a pixel is converted into urban land, which is occupied by the corresponding RA; otherwise, the RA selects the next pixel and enters the bargaining process again, and so on, until the RA successfully selects a residential location. Each iteration represents the selection process of an agent. We used this model to simulate urban expansion within the Wuhan Urban Development Zone (WHUDZ) of central China from 2009 to 2019. The overall accuracy and Kappa coefficient of the simulation results were 92.78% and 55.24%, respectively, which were higher than the results using logistic regression cellular automata. Moreover, we obtained the relative contributions of various influencing factors in the ANN on the residential location selection, revealing the influence of the land acquisition process on land expansion. In addition, the coupled model predicted that the WHUDZ’s urban land area will reach 1415.82 km2 in 2029, mainly through extensional expansion, and the southeast and northwest will be expansion hot spots.

A light robust optimization model for a hierarchical healthcare network

PurposeA growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.Design/methodology/approachMost healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.FindingsThe developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.Originality/valueThe contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.

Risk informed floating storage and re-gasification unit (FSRU) location selection for local natural gas supply

In the present energy market due to high demand of liquefied natural gas (LNG) and the limited availability of land-based LNG import terminals, the use of offshore LNG terminals is destined to increase. Such terminals are referred to as LNG floating storage and re-gasification units (FSRUs). An FSRU terminal is a cost-effective and a time-efficient solution to quickly open up supply to onshore users with minimal environmental impact. This work focuses on the selection from a safety point of view of a possible location for an offshore or nearshore FSRU, given alternative candidate locations. For decision making, the maritime and process safety aspects of the LNG resupply operation have to be considered. This involves the approach of an LNG Carrier (LNGC) to resupply the FSRU. The whole resupply process is divided into three consecutive parts, beginning with the LNGC navigating in the inbound channel, going through its berthing operation, and ending with transfer of the LNG. The safety of the third part, the LNG transfer to the FSRU, could be evaluated by means of a quantitative risk assessment. For the maritime operations this was not possible and evaluation had to rely on expert elicitation. To create a comparison basis of navigating, turning and berthing hazards with the risks of the LNG transfer process, a novel safety utility value (SUV) was defined existing of five ranges. Hazard attributes of navigating and of turning and berthing of the maritime operations were identified/confirmed by simulator runs, their importance was ranked, as well as their safe operating ranges determined with the aid of queries to a large group of experts. Importance ranking was based on pairwise comparison judgment, responses aggregated by means of fuzzy number fits, processed in square matrices. Expert elicitation yielded safety attribute values (SAVs) for the five SUV ranges which were statistically treated. QRA provided potential loss of life (PLL) values, which also were converted into SUV ranges. Based on the importance ranking of the three parts and the SUVs, final results were obtained.

Wetland Vulnerability Metrics as a Rapid Indicator in Identifying Nature-Based Solutions to Mitigate Coastal Flooding

Flood mitigation in low-gradient, tidally-influenced, and rapidly urbanizing coastal locations remains a priority across a range of stakeholders and communities. Wetland ecosystems act as a natural flood buffer for coastal storms and sea level rise (SLR) while simultaneously providing invaluable benefits to urban dwellers. Assessing the vulnerability of wetlands to flood exposure under different SLR scenarios and vegetation responses to climatic variability over time allows for management actions, such as nature-based solutions, to be implemented to preserve wetland ecosystems and the services they provide. Nature-based solutions (NBSs) are a type of green infrastructure that can contribute to flood mitigation through the management and restoration of the ecosystems that provide socio-environmental benefits. However, identifying the flood mitigation potential provided by wetlands and the suitability for NBS implementation depends on the ecological condition and environmental exposure. We propose that wetland vulnerability assessments can be used as a rapid method to quantify changes in ecosystem dynamics and flood exposure and to prioritize potential locations of NBSs implementation. We quantified exposure risk using 100- and 500-year special flood hazard areas, 1–10 ft of sea level rise scenarios, and high-tide flooding and sensitivity using timeseries analyses of Landsat 8-derived multispectral indices as proxies for wetland conditions at subwatershed scales. We posit that wetland areas that are both highly vulnerable to recurrent flooding and degrading over time would make good candidate locations for NBS prioritization, especially when they co-occur on or adjacently to government-owned parcels. In collaboration with local governmental agencies responsible for flood mitigation in the coastal sub-watersheds of the City of New Bern and New Hanover County, North Carolina, we conducted field verification campaigns and leveraged local expert knowledge to identify optimal NBS priority areas. Our results identified several government-owned parcels containing highly vulnerable wetland areas that can be ranked and prioritized for potential NBS implementation. Depending on the biophysical characteristics of the area, NBS candidate wetland types include brackish and freshwater marshes and riverine swamp forests, even though the predominant wetland types by area are managed loblolly pinelands. This study underscores the critical importance of conserving or restoring marshes and swamp forests and provides a transferable framework for conducting scale-invariant assessments of coastal wetland condition and flood exposure as a rapid method of identifying potential priority areas for nature-based solutions to mitigate coastal flooding.

Personalized Route Recommendation With Neural Network Enhanced Search Algorithm

In this work, we study an important task in location-based services, namely <i>Personalized Route Recommendation (PRR)</i> . Given a road network, the PRR task aims to generate user-specific route suggestions for replying to users’ route queries. A classic approach is to adapt search algorithms to construct pathfinding-like solutions. These methods typically focus on reducing search space with suitable heuristic strategies. For these search algorithms, heuristic strategies are often handcrafted, which are not flexible to work in complicated task settings. In addition, it is difficult to utilize useful context information in the search procedure. To develop a more principled solution to the PRR task, we propose to improve search algorithms with neural networks for solving the PRR task based on the widely used <inline-formula><tex-math notation="LaTeX">$A^{*}$</tex-math></inline-formula> algorithm. The main idea of our solution is to automatically learn the cost functions in <inline-formula><tex-math notation="LaTeX">$A^{*}$</tex-math></inline-formula> algorithms, which is the key of heuristic search algorithms. Our model consists of two main components. First, we employ attention-based Recurrent Neural Networks (RNN) to model the cost from the source to the candidate location by incorporating useful context information. Instead of learning a single cost value, the RNN component is able to learn a time-varying vectorized representation for the moving state of a user. Second, we propose to use an estimation network for predicting the cost from a candidate location to the destination. For capturing structural characteristics, the estimation network is built on top of position-aware graph attention networks. The two components are integrated in a principled way for deriving a more accurate cost of a candidate location for the <inline-formula><tex-math notation="LaTeX">$A^{*}$</tex-math></inline-formula> algorithm. Extensive experiment results on three real-world datasets have shown the effectiveness and robustness of the proposed model.

Proposed Optimization Algorithm for Solving CCTV Camera Placement

The installation of CCTV cameras monitoring the street sections of one of the most visited areas of Manila may serve as deterrence against theft, crime, abduction, and even act of lasciviousness. Furthermore, the redundant orientations of some of the units in the system were recognized as possible inhibitors of the efficiency of the local surveillance system. In line with this, the study proposed a model for CCTV camera placement in Intramuros by representing the community as a graph in a 2-dimensional space. The paper presents a two-phase approach in determining the best placements of CCTV cameras. Phase I took care of the ideal installation spots as a set-covering problem while Phase II identified the optimal CCTV orientation using the Proposed algorithm. In Phase I, a binary integer programming model was formulated and solved using the data solver function of Microsoft Excel. The designed algorithm in Phase II was based on greedy heuristics utilizing the results in Phase I to identify the optimal orientation of the CCTV units. Findings suggest that out of the seventeen candidate locations, nine of them are optimal for CCTV installation. A total of twenty-three CCTV units are required to cover all the entry and exit points of the streets in district 5 of Intramuros. The proposed algorithm produced two optimal solutions A and B. Comparison with the existing CCTV system in the district and discussions on each optimal installation suggested that result B is better than A. Recommendations on the results of the study were addressed to the authorities of district 5 for immediate implementation.

Geopolitics and touristrategic borderlands: Balancing nationalism and globalisation in Hainan, China

Little consideration has been given to the contemporary spatial configurations emerging from the expanding intersection between tourism and geopolitics, despite tourism's increasing ubiquity and accelerating geopolitical tension. Using a conceptual case study of China's Hainan Province, this research addresses this gap by introducing “touristrategic borderlands” to describe evolving borderland locations where state governments negotiate a balance between forces of globalisation and nationalism, and hard and soft power, to achieve territorialisation objectives. Reflecting a critical geopolitics of the “everyday”, touristrategic borderlands combine domestic and international tourism with special autonomous zones, amenity and economic migration, connective infrastructure, and militarisation, selectively “weaponising” tourism as strategically warranted. The validity of touristrategic borderlands as a more generally occurring phenomenon is demonstrated by the identification of 12 other candidate locations where all core characteristics except weaponisation (two locations) are found. A transformative governance approach is advocated for dealing with the complexities of touristrategic borderlands.

A Transit-Based Evacuation Model for Metropolitan Areas

This paper develops a decision-support model for transit-based evacuation planning occurring in metropolitan areas. The model consists of two modules executed in a sequential manner: the first deals with determining pick-up locations from candidate locations based on the spatial distribution of the evacuees, and the second plans for the route and schedule for each transit vehicle based on vehicle availability and evacuee demand pattern. An overlapping clustering algorithm is first adopted in allocating the demands to several nearby clusters. Then, an optimization model is proposed to allocate available buses from the depots to transport the assembled evacuees between the pick-up locations and different safety destinations and public shelters. A numerical example based on the city of Baltimore demonstrates the applicability of the proposed model and the advantages compared to state-of-the-art models with overly strict and unrealistic assumptions.

Transit “Pass-Through” Lanes at Freeway Interchanges: A Life-Cycle Evaluation Methodology

Transit “pass-through” lanes provide transit vehicle priority at freeway interchanges. “Pass-through” lanes allow a transit vehicle to exit the freeway at an interchange, cross straight through the intersecting arterial road, and re-enter the freeway. This treatment allows transit vehicles to bypass congestion on the mainline between the beginning of the off-ramp and the end of the on-ramp.This paper outlines a methodology to evaluate if transit “pass-through” lanes are economically justified at a given interchange and provides a method for prioritizing candidate locations. The methodology provides an objective and consistent decision making method, reduces the effort required for practitioners to assess the need for “pass-through” treatment at a given interchange, and helps ensure that limited resources are directed towards interchanges that are expected to experience the greatest benefit per dollar spent.The proposed methodology is based on an analytical approach that compares the value of travel time savings (for passengers and transit vehicles) with the construction and maintenance costs of the transit “pass-through” lane treatment.

Quest for the Australasian impact crater: Failings of the candidate location at the Bolaven Plateau, Southern Laos

AbstractThe quest for the parent impact structure for Australasian tektites (AAT) has remained without solution for almost a century. The present paper doubts the plausibility of the recently proposed location of the impact site at the Bolaven volcanic field in Southern Laos by showing problems with most of the presented lines of evidence. The geochemical incompatibility of the AAT composition with a mixture of weathered basalts and Mesozoic sandstones that were proposed as source materials of AAT is demonstrated by a two‐component mixing calculation for major element oxides and the Nd‐Sr isotopic system. Deficiency of the basaltic component as a source of Ni, Co, Cr, and 10Be in AAT and inconsistency with trends observed for O and Pb isotopes are shown. The size of the putative crater, conclusiveness of a gravity anomaly identification, signs of complete crater burial by postimpact lava flows, and identification of proximal ejecta blanket are doubted. Remarks on the shortcomings of the current consensus location of an impact site for AAT in Indochina are presented.

A Location Recall Strategy for Improving Efficiency of User-Generated Short Text Geolocalization

Currently, users’ daily lives are closely related to social sites. Geolocalizing user-generated short texts (UGSTs) can provide services for the wider fields of business and society. The existing works focus on improving the accuracy of geolocalization algorithms and reducing the prediction error. However, little work has been done on improving the computing efficiency of geolocalization algorithms. When dealing with large-scale data, the existing algorithm efficiency is greatly reduced. To solve this problem, we summarize three modes of user access to point of interests (PoIs), further propose a variety of location recall methods, and then introduce these geolocation recall methods into the existing algorithm. Geolocation recall generates a candidate location set for each user according to the user’s historical behavior records to reduce the search space of the geolocalization algorithm and improve its efficiency. We carried out experiments on the ground-truth datasets, compared the performance of various location recall methods, and verified the excellent location recall performance of three geolocalization algorithms. The experimental results show that location recall shortens the calculation time of the three algorithms by approximately 70% and further improves the accuracy of these algorithms.