Location Selection Model Research Articles

Selecting the field hospital location for earthquakes: an application for Ankara Province in Turkey

PurposeThe authors present a location selection model for the field hospital to build after a possible earthquake in Ankara, Turkey using the VIKOR method.Design/methodology/approachCompanies or governments that make location selection decisions to improve their performance in new investment decisions for different service industries. On the other hand, disasters, especially earthquakes, force the governments to evaluate their existing potentialities and develop action plans to improve their middle and long-term preparations. This paper proposes a VIKOR method-based location selection model for the field hospital to build after a possible earthquake. Also, the authors present a methodology using the VIKOR method that how government agencies take action for the field hospital's location selection process via VIKOR methodology.FindingsThe modeling and application results show that the field hospital's location selection decision-making process improves considerably using the VIKOR model. This paper shows that the proposed VIKOR-based model can rank alternatives suitability at various criteria targeting to minimize the possible earthquake's impact and obtains a single overall ranking score to select the best alternative.Research limitations/implicationsThe study does not consider the uncertain nature of the field hospital selection problem. The application part is restricted to the Ankara case. But the proposed model can easily extend for different locations in the world.Originality/valueThis paper presents the multi-criteria decision-making (MCDM) framework study of the establishment of field hospitals and demonstrates its importance when criteria diversity is restricted.

A hybrid model for distribution center location selection

This research aims to propose an integrated MCDM model to support the distribution center location selection. The integrated approach of ANP and TOPSIS was employed to address the distribution center selection problem. The ANP method was used to define the weights of the selection criteria, whereas the TOPSIS was applied to rank alternatives. The proposed model was then applied into Dong Nai province in Vietnam to select the best alternatives to be the distribution center. The results showed that Long Khanh is the most appropriate location for the distribution center as it is ranked first in the order of preference for selection. The proposed model provides the decision makers with more powerful methods than conventional ones. Therefore, the model can be applied to distribution center location selection in all industries. In terms of theoretical contribution, the proposed criteria can contribute to literature review in the selection of location as well as the concept of distribution center. In addition, the research also provides insight for firms and public authorities in making decision on distribution center location based on limited resources as well as avoiding the misuse of funds.

Impact of Shared Bus on Campus Travel and Space Optimization Based on Activity Travel Behavior

Based on the travel analysis of students in the Jiulonghu campus, this paper constructs a small-scale shared bus in the campus, explores the impact of shared traffic on campus travel, promotes the optimization design of campus space environment, and creates a more comfortable and convenient travel space. In order to overcome the shortcomings of the traditional trip-based research, this paper analyzes travel behavior from the perspective of activity-based travel concept framework, considering more activities and travel information. At the same time, in order to improve the richness of information, the explicit preference survey (RP) and the declarative preference survey (SP), which are added to the bus sharing customized travel platform, are used to collect data of personal attributes and travel diary. Firstly, based on the ArcGIS platform, this paper constructs the activity travel path generation tool, dynamic activity density distribution tool, and spatiotemporal path clustering tool and comprehensively analyzes the activity travel mode from the aspects of time distribution, spatial distribution, and category characteristics. Secondly, based on the travel activities, the location selection model (S-MNL) considering the heterogeneity of SP and RP data sources and the activity duration planning model (Cox regression), considering the nonnormal distribution of activity duration are established to analyze the impact of shared bus on students’ travel distance, travel time, and travel frequency. Finally, according to the analysis of modeling results, the impact of shared traffic on campus travel is analyzed, and the optimal design scheme of campus space is given. This paper uses the survey method based on declarative preference SP and the survey method based on explicit preference (RP) to get the actual and hypothetical travel response of travelers, which improves the data richness.

COMBINING BOOTSTRAPPING AND GENETIC ALGORITHM BASED ON FEATURE SELECTION FOR FRANCHISE LOCATION PROSPECTS PREDICTION

Location selection is crucial in the franchise fast-food industry. A thorough location selection model paired with a proper analytical technique can considerably improve the performance of placement decisions, attract more customers, and raise market share and profitability. Franchise location data sets have an imbalanced class nature. The franchise location prospect prediction performance decreased as a result of the dataset's noisy characteristics. We developed a hybrid approach to improve franchise location prospect prediction performance in this study. It combines Bootstrapping to address class imbalance problems and Genetic Algorithm (GA) to select relevant features in the franchise location prospect prediction. We experimented with four different classification methods (Naive Bayes, C4.5, Random Forest, ID3, Gradient Boosted Trees). The results show that almost all classifiers that use Bootstrapping and GA outperform the original technique. We employ the Confusion Matrix and Root Mean Squared Error (RMSE) to examine the proposed method's performance. The test results demonstrate that the proposed method considerably enhances the franchise location prospect's classification performance.

Landfill location selection for healthcare waste of urban areas using hybrid BWM-grey MARCOS model based on GIS

Healthcare waste generated by medical activities in big cities includes a vast spectrum of materials, from blood, body parts, medical devices, pharmaceuticals, chemicals, diagnostic samples, soiled dressings, syringes and needles, and radioactive material. Improper management of health-care waste places the urban community and society, urban residents, patients, and water resources at risk from the toxic effects of environmental pollution, which can bring up many social and environmental costs for municipalities. Location selection for sitting a landfill for health-care waste with a sustainable development perspective is a complicated decision making problem in the urban and social planning area. This study develops a novel integrated decision-making model for landfill location selection for the health-care waste system. In this study, Geographic Information System (GIS), Best-Worst Method (BWM), and Measurement of alternatives and ranking according to COmpromise solution (MARCOS) method under grey interval set considering sustainability factors. To generate the GIS suitability maps, location criteria are first calculated using the BWM model. The GIS suitability maps suggest eight potential locations for landfilling, which are prioritized using G-MARCOS in order to select the best alternative location. To the best of our knowledge, the present study is the first study to integrate GIS, BWM, and G-MAROCS methods for sustainable landfill location selection problem for health-care waste. This paper investigates a real case of the municipality of Hamedan, Iran, to show the applicability of the developed methodology for urban planning problems. Sensitivity analysis tests are performed to establish the reliability and robustness of the results. Alternative A7, A8, and A4 are selected respectively as the top three potential location for sitting a landfill for health-care waste. However, locations A6, and A1 are the least suitable alternatives for sitting in a landfill.

Decision-making for location of manufacturing bases in an uncertain demand situation

Multi-site selection is a hot research issue for equipment manufacturing enterprises. With the development of smart industry, equipment manufacturing enterprises have entered the era of personalized and small batch manufacturing. Enterprises want to better meet customer needs and win competition, they must carry out scientific factory planning and site selection, so as to ensure quick response to the market. Based on this, this paper proposes a two-stage location selection model. Firstly, the method uses fuzzy numbers to express the demand size of demand points. Secondly, the distance factor is used as a criterion to select the candidate manufacturing bases with sufficient available resources. Next, the location model of enterprise manufacturing base is established which the goal of maximizing service efficiency and the constraints of time, cost and demand. Finally, a random numerical example is used to simulate the model, and lingo is used to solve it.

Research on Location Selection Strategy for Airlines Spare Parts Central Warehouse Based on METRIC.

With the increased demands of airlines, it is important to study the location selection strategy for spare parts central warehouse in order to improve the allocation capacity of spare parts maintenance resources and reduce the operating costs of airlines. Based on the M/M/s/∞/∞ multiservice desk model and Multi-Echelon Technique for Recoverable Item Control (METRIC) theory, this paper proposes a spare parts supply strategy based on the spare parts pool network and establishes a location selection model for spare parts central warehouse. The particle swarm optimization (PSO) algorithm is used to iteratively optimize the location for spare parts central warehouse and adjust the location area of the central warehouse combining transportation facilities and geographical environment factors. Finally, the paper compares the operating results for multiple airlines in pooling and off-pooling states and verifies the effectiveness of the spare parts supply model and the advantages of cost control for airlines.

异构群体信息下基于后悔理论的前置仓选址模型研究

异构群体信息下基于后悔理论的前置仓选址模型研究

Reverse logistics of municipal solid waste------Study on the Location of transfer stations

Reverse logistics optimization design for recyclable municipal solid waste is a social and economic problem. This paper mainly studies the location problem of reverse logistics network transfer station, which involves how to select the most effective location from the set of points to be selected. In this paper, an improved P median location selection model is proposed on the premise of minimizing the impact on residents, and greedy extraction heuristic algorithm is adopted to solve the model. Finally, the effectiveness of the model in the construction of MSW reverse logistics site selection is illustrated through an example analysis, and theoretical reference is provided for the actual site selection problem.

A hierarchical flood shelter location model for walking evacuation planning

ABSTRACT Prior planning of shelters and evacuation routes is the foundation of effective and safe post flood management. In this study, a hierarchical model for emergency shelter location selection in preparation for immediate, short-term, and long-term floods was developed. To ensure the safety of evacuation routes, levels of walking evacuation risk were classified based on inundation depth and flow rate, and high-risk areas were set as barriers in the network analysis. Accessibility, safety from inundation, service accessibility, and facility capacity were set as criteria for location selection to ensure evacuation safety and the capacity to provide the services necessary to maintain the lives of evacuees in shelters. Candidate locations in a flood shelter case study area were selected, and their characteristics compared with those of existing designated shelters via a grading system. The candidate shelters were found to be preferable in terms of safety and service capacity. The model presented here considers the viability of walking evacuation on flooded roads and a selection of methodologies for each type of flood shelter, thereby providing insight into the design of an integrative model to address the complex decision-making processes involved in flood shelter selection and post-flood management.

Research on the Location selection of Logistics Transshipment Center base on “16+1 Cooperation”

Since the launch of the “16+1 Cooperation”, political mutual trust between China and Central and Eastern Europe Countries (CEECs) has been increasing, and economic cooperation relationship has continued to advance. Aiming at the demand of international strategic development ‘going global’, this paper analyzes the development trend of logistics and establishes a mathematical model for location selection of the logistics transshipment center of Chinese enterprise based on the demand of cargos and the transportation distance. According to the total trade volume of the CEECs from 2013 to 2017, the paper introduces the Artificial Fish Swarm Algorithm (AFSA) to solve the model and finds the optimal logistics transshipment centers under different number of locations. The results show that AFSA is suitable for location selection of the logistics transshipment centers and can provide an important reference for China’s logistics enterprises.

Development of an integrated decision making model for location selection of logistics centers in the Spanish autonomous communities

Logistics centers are those areas where all the national and international logistics and transportation operations are managed and directed to various business operations. One of the essential elements of an urban development system is to identify the appropriate location for a logistics center. In practice, the issue of evaluating and selecting the most suitable geographical area for a logistics center is considered as a complex decision making problem that can be well formulated through analytical and mathematical models. An exhaustive review of literature indicates that no concrete study has still proposed any integrated evaluation approach for logistics center selection. Thus, this paper aims in developing a two-stage decision making model to find out the most preferred zone in the autonomous communities of Spain for establishment of logistics centers. In the first stage, the considered communities are compared based on five evaluation criteria using data envelopment analysis (DEA) to identify the efficient and inefficient alternatives. In the second stage, a model is designed to evaluate the performance of the efficient communities using rough full consistency (R-FUCOM) and combined compromise solution (R-CoCoSo) methods. The adopted model allows capturing the uncertainty and vagueness in the decision makers’ judgments as involved in the evaluation process with the use of rough set theory (RST). The R-FUCOM method is utilized to obtain the optimal weights of the criteria, while R-CoCoSo method is finally used to rank the efficient communities. In addition, sensitivity analyses are performed to validate the robustness of the derived results.

Location selection of emergency supplies repositories for emergency logistics management: A variable weighted algorithm

With the development of the city, the number of establishments that are proposed or under construction is increasing year by year, and if they are industries that handle flammable, explosive, toxic, harmful, and dangerous substances, the public safety will face great threats, which will bring great challenges to emergency rescue work. Therefore, providing reasonable solutions to the problem of location selection of emergency supplies repositories are necessary for improving the emergency response efficiency in chemical industrial parks. A mathematical model for location selection of emergency supplies repositories in emergency logistics management are presented considering more actual factors. The optimization objectives of the model are to minimize total transport length and cost. And then a Variable Weighted Algorithm is designed to solve the model, where an auxiliary function was constructed with different methods of building weighting factors based on the theory and method of solving multi-objective optimization problems in operational research. Simulation results show the effectiveness and feasibility of the models and algorithms presented in this paper.

The Study of a Multicriteria Decision Making Model for Wave Power Plant Location Selection in Vietnam

With about a 7% average annual economic growth rate in Vietnam, the demand for electricity production is increasing, and, with more than 3000 km of coastline, the country has great potential for developing wave energy sources to meet such electricity production. This energy source, also known as renewable energy, comes from tides, wind, heat differences, flows, and waves. Both wind and wave energy are considered to have the most potential for energy sources in Vietnam. Just as hydropower projects are controversial due to depleting water resources and regulating floods, nuclear power projects cause safety concerns. To overcome this problem, Vietnamese scientists are considering using abundant wave energy resources for electricity. Nowadays, the ocean energy sector offers many new technologies to help minimize carbon dioxide emissions (CO2) in the living environment. Further, many countries already have wave power plants. In this research, an integrated model, combining the fuzzy analytical network process (FANP) and the technique for order of preference by similarity to ideal solution (TOPSIS), is proposed for wave energy plant location selection. As a result, Con Co (SITE3) is determined the best site for wave energy production. The primary aim of this study is to provide insight into site selection problems for renewable energy investments of Vietnam. The contribution of this research is to propose a fuzzy multiple-criteria decision-making (MCDM) model for site selection in the renewable energy sector. The proposed model also can address different complex problems in location selection; it is also a flexible design model for considering the evaluation criteria; further, it is applicable to site selection of other renewable energies in the world.

Research on location selection model of distribution network with constrained line constraints based on genetic algorithm

With the rapid rise of the Internet, China’s e-commerce has also flourished. The development of e-commerce has led to an increase in the volume of logistics and distribution. The further development of e-commerce has also placed higher demands on the timeliness of logistics and distribution. The competition of e-commerce companies has shifted from the competition between business models to the competition between logistics services. The scientific and rational distribution site selection planning is the prerequisite and guarantee for the efficient operation of logistics distribution network. To balance the contradiction between logistics distribution speed and distribution cost has become the key to competition among e-commerce companies. This paper analyzes the current network structure and distribution mode of e-commerce logistics city distribution, and analyzes and discusses the problems existing in current e-commerce logistics city distribution. Furthermore, the bi-level programming is studied. According to the characteristics of the bi-level programming problem, the genetic algorithm flow suitable for bi-level programming is proposed. The bi-level programming model of urban distribution service network site selection with limited lines is proposed. Through the verification of the genetic algorithm in this paper, the proposed method can plan a reasonable service site location layout and distribution models and path selection. The results show that the average daily fuel cost can be reduced by 37.6%, and the transportation distance and fuel cost can be optimized best.

Model for location selection of traffic sign setting in road intersection of mountainous city based on driving characteristics analysis

ABSTRACTThere are many intersection roads in the urban road, and the intersection is often a necessary place for the vehicle to complete the swerve and for the agminated foot passengers to across the street. Most of the roads in mountainous cities have deformed intersections. Therefore, the location selection of traffic signs at a mountain road intersection is particularly important. Based on the driving characteristics, this paper discusses the location selection of related traffic signs at the intersection. According to the brief analyses on intersection characteristics in mountainous city and based on drivers' specific visual reaction, the related visual dynamic states for drivers are determined. On the strength of drivers’ visual reference frame, the specific location of traffic sign at road intersection in mountainous city is installed.

Multi-Criteria Decision Making (MCDM) Approaches for Solar Power Plant Location Selection in Viet Nam

The ongoing industrialization and modernization period has increased the demand for energy in Viet Nam. This has led to over-exploitation and exhausts fossil fuel sources. Nowadays, Viet Nam’s energy mix is primarily based on thermal and hydro power. The Vietnamese government is trying to increase the proportion of renewable energy. The plan will raise the total solar power capacity from nearly 0 to 12,000 MW, equivalent to about 12 nuclear reactors, by 2030. Therefore, the construction of solar power plants is needed in Viet Nam. In this study, the authors present a multi-criteria decision making (MCDM) model by combining three methodologies, including fuzzy analytical hierarchy process (FAHP), data envelopment analysis (DEA), and the technique for order of preference by similarity to ideal solution (TOPSIS) to find the best location for building a solar power plant based on both quantitative and qualitative criteria. Initially, the potential locations from 46 sites in Viet Nam were selected by several DEA models. Then, AHP with fuzzy logic is employed to determine the weight of the factors. The TOPSIS approach is then applied to rank the locations in the final step. The results show that Binh Thuan is the optimal location to build a solar power plant because it has the highest ranking score in the final phase of this study. The contribution of this study is the proposal of a MCDM model for solar plant location selection in Viet Nam under fuzzy environment conditions. This paper also is part of the evolution of a new approach that is flexible and practical for decision makers. Furthermore, this research provides useful guidelines for solar power plant location selection in many countries as well as a guideline for location selection of other industries.

Strategic model for location selection of solar wood drying by applying TOPSIS

The location of solar wood drying has not been selected in Iran yet. One of important applications of solar energy is to manufacture solar wood drying units. Effective indicators in location of solar wood drying were identified and a hierarchy was constructed based on five major groups of criteria. The weights of the indicators were then established by Analytical Hierarchy Process. The amounts of the indicators with regard to provinces were obtained from wood drying factories in public and private sectors. These weights were employed in TOPSIS to rank the provinces. Finally the potential provinces were identified according to the priorities obtained by this technique. The results showed that Qom Province, has the best priorities for establishment of solar wood drying.

Variable Message Sign Location Selection Basing on Drivers’ Perception

Abstract Variable Message Sign (VMS) location has impacts on the total travel time of transportation network. However, drivers with various characters have different understanding on each route travel time under information conveyed through VMS, which leads to different route choice behaviors, especially for schematic VMS. So VMS guidance may lead to induced congestion and increase the total travel time when drivers’ perception isn’t considered. To address this problem, a VMS location selection model basing on drivers’ responses to schematic VMS and their satisfaction degrees to VMS-based information service is proposed to minimize the total travel time. And a case study of Jiading New Town indicates that the total travel time decreases as drivers’ compliance rates rise. But the rate of descend declines gradually. And the total travel time keeps steady when drivers’ compliance rates approach 1, which indicates that VMS-based total travel time reduction decreases with drivers’ compliance rates increasing. However, VMS is effective on reducing the total travel time even though drivers’ compliance rates are lower than 1.

Selection Of Multi-Distribution Center Location Based On Low Carbon

With the increasing of logistics activity, the influence of vehicle emissions for air quality is more and more serious. As the hub of logistics system, distribution center affects all aspects of the logistics vehicles directly. Such as vehicle number, road load, vehicle route and so on. As a result, Distribution center also plays a decisive role on carbon emissions. However, the traditional distribution center can rarely meet the needs of current low carbon society development, because they hardly consider energy conservation and emissions reduction when choose the location. Basing on the traditional distribution center location selection, this paper structures a location selection model of multiple distribution centers under the comprehensive consideration of low carbon, service optimization and cost saving. This paper also optimizes the distribution center location depending on economic cost minimization as the target, uses the improved genetic algorithm coding, and validates the feasibility and effectiveness by example verification model.