Site Selection Issues Research Articles

An Improved Strategy to Effectively Manage Healthcare Waste after COVID-19 in Republic of Korea

During the coronavirus disease 2019 (COVID-19) pandemic, 24,289 tons of infectious waste was generated in 2021 in Korea, a 320% increase compared to that generated in 2020 (5788 tons). The disposal of other healthcare waste has been delayed because COVID-19 infectious waste must be disposed of first, leading to long-term concerns related to the lack of healthcare waste disposal capacity. To solve this problem, this study investigated healthcare waste classification systems in Korea and overseas. We analyzed the current state of healthcare waste in Korea and compared the treatment methods and healthcare waste treatment systems by country. The results showed that Korea has a strict healthcare waste management system compared to other countries, which relies on dedicated incinerators and transport. It is difficult to expand incinerators exclusively for healthcare waste due to site selection issues because they incinerate infectious waste. Therefore, to solve the healthcare waste disposal problem, Korea should improve its management system to reduce treatment amounts. This study suggests that general healthcare waste that is considered less infectious should be excluded from healthcare waste-exclusive treatment and that sterilization/grinding as an intermediate treatment method should be allowed.

Single-Valued Neutrosophic Sets Based Score Function and WASPAS Method for Plant Location Selection Problem

In the context of single-valued neutrosophic sets (SVNSs), where the weights of the criteria are unknown, this work seeks to provide an integrated technique based on Entropy and Weighted Aggregate Sum Product Assessment (WASPAS) methodologies. A numerical case study (the plant site selection issue) is used to establish precise values for the criteria. We initially "fuzzify" the decision matrix before transforming it into an SVNS- decision matrix. The SVNS entropy weight technique is used to assign weights to each criterion. The scoring function is used by a tweaked version of the WASPAS algorithm to choose the optimal solution. The subject under study has also been applied to other MCDM methods, such as the more prevalent VIKOR and MOORA procedures. The SVNS-VIKOR technique has also been applied to the issue at hand. Using the same illustrative scenario, this study evaluates the strengths and weaknesses of several methods for verifying the accuracy of previously published data. The usefulness and efficiency of the used strategy are highlighted by the comparison study. When applied to real-world situations, the suggested method shines because it yields reliable findings even though the underlying data is plagued with issues such as uncertainty, imprecision, indeterminacy, and inconsistency.

Evolved distance measures for circular intuitionistic fuzzy sets and their exploitation in the technique for order preference by similarity to ideal solutions.

Circular intuitionistic fuzzy (C-IF) sets are an up-and-coming tool for enforcing indistinct and imprecise information in variable and convoluted decision-making situations. C-IF sets, as opposed to typical intuitionistic fuzzy sets, are better suited for identifying the evaluation data with uncertainty in intricate realistic decision situations. The architecture of the technique for order preference by similarity to ideal solutions (TOPSIS) provides powerful evaluation tools to aid decision-making in intuitionistic fuzzy conditions. To address appraisal issues associated with decision analysis involving extremely convoluted information, this paper propounds a novel C-IF TOPSIS approach in the context of C-IF uncertainty. This research makes three significant contributions. First, based on the three- and four-term operating rules, this research introduces C-IF Minkowski distance measures, which are new generalized representations of distance metrics applicable to C-IF values and C-IF sets. Such general C-IF distance metrics can alleviate the constraints of established C-IF distance measures, provide usage resiliency through parameter settings, and broaden the applicability of metric analysis. Second, unlike existing C-IF TOPSIS methods, this research fully utilizes C-IF information characteristics and extends the core structure of the classic TOPSIS to C-IF contexts. With the newly developed C-IF Minkowski metrics, this study faithfully demonstrates the trade-off evaluation and compromise decision rules in the TOPSIS framework. Third, this research builds on the core strengths of the pioneered C-IF Minkowski distance measures to create innovative C-IF TOPSIS techniques utilizing four different combinations, including displaced and fixed anchoring frameworks, as well as three- and four-term representations. Such a refined C-IF TOPSIS methodology can assist decision-makers in proactively addressing increasingly sophisticated decision-making problems in practical settings. Finally, this research employs two innovative prioritization algorithms to address a site selection issue of large-scale epidemic hospitals to illustrate the superior capabilities of the C-IF TOPSIS methodology over some current related approaches.

A circular intuitionistic fuzzy evaluation method based on distances from the average solution to support multiple criteria intelligent decisions involving uncertainty

This study aims to construct an evaluation method based on distances from the average solution (EDAS) based on circular intuitionistic fuzzy (C-IF) sets to support intelligent decision-making involving multiple criteria and intricate uncertainty. C-IF sets possess a resilient circular structure that can model decision-makers’ hesitancy and indecision like intuitionistic fuzzy sets and can add ambiguity to fuzzy membership and nonmembership functions like type-2 fuzzy sets. Related to the existing literature on EDAS in uncertain environments, a new interpretation is needed so that the decision assistance procedure can exploit higher-order fuzzy membership functions as well as in type-2 fuzzy settings, and can address decision hesitancy as well as in IF settings. However, EDAS has not been studied to discuss its applicability in C-IF circumstances and make headway a suitable extension model, which forms a research question worth exploring. To address this issue, this study endeavors to construct a C-IF EDAS methodology and propound novel concepts and measurements that can improve the core techniques of traditional EDAS, enabling them to handle complicated C-IF information and treat highly equivocal and indistinct decision-making tasks. The C-IF analytical procedure for decision-making is mainly built upon two representations from semantic assessments, namely C-IF assessment ratings and C-IF importance weights. This study puts forth the concept of aggressive and conservative estimates to identify anchored datum-based measurements that provide new interpretations of positive distance and negative distance concerning the C-IF average solution; besides this study evolves an extended EDAS decision rule in C-IF circumstances. Based on an aggregated operation and a membership score function, anchored datum-based (normalized) weighted sums about positive/negative distances can be rendered to produce a joint appraisal score for a compromise ranking of available alternatives. To corroborate the applicability of the established notions and measurements, this study utilizes the C-IF EDAS model and decision procedure to tackle a realistic site selection issue for a pandemic hospital within C-IF environments. The suitability, robustness, and flexibility of the developed C-IF EDAS methodology are confirmed through some comparative analyses and experimental studies. First, this study verifies the correctness and trustworthiness of the executive outcomes from the viewpoints of membership, nonmembership, and vague score functions. Next, this study confirms the effectuality and rationality of the proposed C-IF EDAS by comprehensive comparison with several related methods. Furthermore, this study suggests a flexible way of setting appraisal and distance parameters in the C-IF EDAS to facilitate intelligent decision-making in reality. Finally, some conclusive discussions of the C-IF EDAS solution are systematically investigated to reveal its practicality and application merits in the realm of multiple criteria decision analysis with information uncertainty; it is also confirmed that the C-IF set is well suited as a fundamental of problem modeling within complex decision-making environments.

Emergency airport site selection using global subdivision grids

ABSTRACT The occurrence of large-magnitude disasters has significantly aroused public attention regarding diversified site selection of emergency facilities. In particular, emergency airport site selection (EASS) is highly complicated, and relevant research is rarely conducted. Emergency airport site selection is a scenario with a wide spatiotemporal range, massive data, and complex environmental information, while traditional facility site selection methods may not be applicable to a large-scale time-varying airport environment. In this work, an emergency airport site selection application is presented based on the GeoSOT-3D global subdivision grid model, which has demonstrated good suitability of the discrete global grid system as a spatial data structure for site selection. This paper proposes an objective function that adds a penalty factor to solve the constraints of coverage and the environment in airport construction. Through multiple iterations of the simulated annealing algorithm, the optimal airport construction location can be selected from multiple preselected points. With experimental verifications, this research may effectively and reasonably solve the emergency airport site selection issue under different circumstances.

Development of an optimization-aided small modular reactor siting model – A case study of Saskatchewan, Canada

As an emerging clean technology, the replacement of coal plants and the integration with renewable power generation are two appealing options for the deployment of SMRs in the power system. However, both these applications and SMR siting issues for power systems have multiple complexities that have been difficult to be considered in past studies. Accordingly, an optimization-aided small modular reactor siting (OASS) model is initiated in this study to support decisions of siting, sizing, and timing for small modular reactor (SMR) development. The proposed OASS model is specialized for obtaining possible SMRs siting schemes, wind-SMRs combination schemes, and power system transition schemes with coal plant closure and SMRs deployment. This research initiates the application of an optimization-based modelling approach to tackle SMRs site selection issues for Saskatchewan, Canada. The results disclose that electricity imports and natural gas power will fill the electricity demand gap in Saskatchewan’s power system in the short term. Results obtained from this model can also identify optimized patterns of SMRs and wind farms deployment and siting in Saskatchewan. Power stations with large capacity and independent transmission grid will become the primary choice in the SMRs and wind farms site selection process. Such patterns and alternatives would enable decision-makers obtain optimized energy structure by introducing SMR reflecting trade-offs between overall system costs and greenhouse gas (GHG) emissions from both economic and environmental perspectives.

A grey approach to site selection for nursing homes: An extension of the fuzzy analytic hierarchy process

The construction of more nursing homes has become one of the most needed pension services in China, and the issue of site selection is one of the most important steps in their construction. The problem of site selection for nursing homes is a complex system engineering problem that involves not only economic interests but also social interests. Due to the limitations of human thinking in the evaluation process, the evaluation value of a nursing home site might be an interval grey number. Moreover, the evaluation indicator system for nursing home locations is a two-layer system that has been neglected in the literature. Therefore, the fuzzy analytical hierarchy process is extended to a new grey approach, i.e., the grey analytic hierarchy process, which can solve the evaluation problems for a two-layer indicator system under an interval grey environment. By constructing a three-point interval grey number, grey evaluation criteria are given to obtain a judgment matrix for interval grey numbers. Definitions of the initial weights, nongreyness weights and integrated weights are proposed to find the best evaluation object. Finally, the effectiveness of the method proposed by this paper is verified by comparative analyses of other grey methods.

Systematic Review of Site-Selection Processes in Onshore and Offshore Wind Energy Research

Wind energy has a leading role in achieving a low-carbon or completely carbon-free energy sector in the near future. Scientific research on the site-selection aspects of onshore and offshore wind farms is of great importance, contributing to sustainable, technically and economically viable, and socially acceptable wind energy projects. This systematic review provides direct analysis and assessment of existing site-selection procedures and addresses a gap in knowledge in the onshore and offshore wind energy research field, identifying trends in the thematic modules of site-selection issues. Important insights and useful trends are highlighted in: (1) site-selection methodologies; (2) the type, number, and exclusion limits of exclusion criteria; (3) the type, number, importance, priority, and suitability classes of assessment criteria; (4) studies’ geographic locations; (5) spatial planning scales; (6) wind resource analysis; (7) sensitivity analysis; (8) participatory planning approaches, groups, and contributions; (9) laws, regulations, and policies related to wind farm siting; (10) suitability index classifications (i.e., linguistic and numeric); and (11) micro-siting configuration of wind turbines. Identified insights and trends could motivate the conduction of updated site-selection analyses on onshore and offshore wind energy research, addressing the determined gaps and enhancing global siting implementations.

Evaluating the Distribution of Health Services in Nasiriyah City By Utilizing Geomatics Techniques

The growth of cities is one of the most important global phenomena, which is occurring under the influence of environmental factors on the human, economic and political, and giving services to citizens and the city are of the priorities of the urban planners and managers. To accomplish this, a variety of techniques have been used both classical and modern the use of quantitative methods in problems locating utilities increased and each of these methods in addition to the advantages and disadvantages in this field is used to study how the spatial distribution of health facilities in Nasiriyah city, has been studied as the case the system uses a multi-criteria analysis. The issue of site selection, service, and service centers in the city is better. The purpose of this study is to evaluate the efficiency of the current distribution of health services by using GIS and Population criterion is analytical and descriptive methods and the type of application. To achieve this objective the integration of GIS and hierarchical method (AHP) and GIS was used, the required layers, including the proximity to compatible land uses, access to the Road network, population density, Spatial distribution, Create an integrated database of health service sites to be established in the future to assist decision-makers and planners to for take decision-making. After conducting the analysis using the two criteria (population density and Spatial distribution ), the results were found, most of which was the apparent deficiency in the current health services, the city’s need for various types of health services.

Site selection of wind farms using GIS and multi-criteria decision making method in Wafangdian, China

Abstract Site selection is one of the most significant decision making activities for development of wind energy resource. In this study, a novel method integrating Geographic Information System (GIS), interval Analytic Hierarchy Process (IAHP) and stochastic VIKOR was proposed to tackle site selection issue of wind farms in the Wafangdian region, China. Two major factors, i.e. biodiversity conservation and production safety, were utilized to determine feasible areas. Afterwards, the weight of evaluation criteria, including the social impact, economic benefit, terrain and eco-environment protection, were identified by using IAHP. Finally, the suitability indexes of various alternatives were calculated by stochastic VIKOR and their ranking was used to determine high-suitability areas for wind farm locations. The obtained results indicated that 30.2% of studied region were suitable for installing the wind-power facilities, but only 3.36% were determined to be highly suitable. By comparing the optimized results to the actual locations of existing wind farms, it was revealed that the ideological framework of this study were practical and effective in guiding site selection of wind farms, and they were also useful for applications in site selection of other renewable energy forms involving complex spatial analysis and multiple criteria evaluation, including solar, hydroelectric, geothermal and biomass.

Site Selection Improvement of Retailers Based on Spatial Competition Strategy and a Double-Channel Convolutional Neural Network

The issue of site selection has become a critical challenge in the development of the retail industry with the growth of the Chinese economy and the improvement in the level of household consumption. Previous studies have considered the area of stores as the main factor of retail competition; however, the actual business performance of different stores in these studies was ignored. In addition, few studies have considered the differences in the spatial distribution of the factors of site selection. In this study, we discuss the improvement of site selection of small retail shops. A spatial competition index model was proposed as one of the features in estimating region market potential, and a market demand regression model of a double-channel convolutional neural network (CNN) was constructed based on the spatial correlation range of features. The study area was Guiyang, China. The experiments were based on the monthly sales data of fast-moving consumer goods retail stores in Guiyang. On the basis of the estimated results of the model, 18 sites with high potential for market demand were recommended. The performance of the proposed model was the best among well-known regression methods. Moreover, in comparison with a single-channel CNN, the proposed model decreased the root mean square error by 22.61%. Evaluation results showed that the proposed method could provide effective decision support for the issue of retail site selection.

Hybrid PSO-WDBA method for the site selection of tailings pond

The disposal of tailings is a vital process in mines. This study aims to address site selection issue of tailings pond using a suitable method. First, as different types of evaluation criteria exist, hybrid decision making information is considered. That is, crisp numbers are used to express quantitative values, while picture fuzzy numbers (PFNs) are suggested to describe qualitative information. Moreover, new comparison methods of PFNs are introduced to overcome the existing limitation. Considering the situation where weight information is partly known, a nonlinear optimization model is constructed. Then, to calculate criteria weights, the particle swarm optimization (PSO) algorithm is modified by introducing penalty functions. Afterwards, the weighted distance based approximation (WDBA) method is extended with hybrid evaluation information to rank alternatives. Last, the hybrid PSO-WDBA technique is applied in selecting the best tailings pond site in a gold mine. The effectiveness and advantages of this method are also verified through detailed discussions. The results show that the proposed evaluation model is dependable and effective, and can provide references for the site selection and management of tailings pond.

Current Issues of Site Selection in the Global Economic Space

Current Issues of Site Selection in the Global Economic Space

Site selection of high-speed railway station: A trapezoidal fuzzy neutrosophic-based consensual group decision-making approach

The need of quick and comfortable public transportation in our societies makes that many countries are planning to develop a high-speed railway network for improving their passenger transport capacity. Such a development implies among other problems how to select the location of high-speed railway station (HSRS) in each city along the line? Thus, this paper introduces an integrated approach for solving the site selection problem of HSRS, which consists of a consensus reaching process (CRP) with a group decision making (GDM) method whose inputs are trapezoidal fuzzy neutrosophic set to model experts’ assessments of potential locations of HSRS. To accomplish the decision process, the inputs should be weighted and aggregated with novel trapezoidal fuzzy neutrosophic prioritized aggregation operators to reflect the priority relationship between the aggregated information. The necessity of polishing conflicts in these decisions lead then to improve the experts’ agreement in the group, in our case, three consensus indexes at different levels are defined to implement the CRP. Eventually, the proposed CRP-GDM approach is put forward to solve the site selection issue of HSRS and a case of study is presented to illustrate its applications and advantages.

An integrated GIS and robust optimization framework for solar PV plant planning scenarios at utility scale

Today, the overall goal of energy transition planning is to seek an optimal strategy for increasing the share of renewable sources in existing power networks, such that the growing power demand is satisfied at manageable short/long term investment. In this paper we address the problem of PV penetration in electricity networks, by considering both (1) the spatial issue of site selection and size, and (2) the temporal aspect of hourly load and demand satisfaction, in addition with the investment and maintenance costs to guarantee a viable and reliable solution. We propose to address this spatio-temporal optimization problem through an integrated GIS and robust optimization model, that allows handling of the ubiquitous dependencies between resource and demand time variability and the selection of optimal sites of renewable power generation. Our approach contributes to the integration of the multi-dimensional and combinatorial aspects of this problem, gathering geographical layers (regional or national scale) and temporal packing (hourly time stamp) constraints, and cost functions. This model computes the optimal geographical location and size of PV facilities allowing energy planning targets to be met at minimal cost in a reliable manner. In this paper, we illustrate our approach by studying the penetration of large-scale solar PV in the French Guiana’s power system. Among the results, we show for instance that: (1) our approach performs geographical aggregation with real contextual data, i.e. balances the intermittency of RE sources by spreading out the corresponding installations (location + size) across the territory; (2) the total installed PV capacity can be doubled by removing the 35% penetration limit on intermittent power without exceeding hourly demand; (3) the safest investment scenario is below 30MW of new PV facilities (≈45M€ and 2 plants), though it is theoretically possible to install up to 45MW (>120M€ and 11 plants).

A collaborative spatial decision support system applied to site selection problems

Nowadays, urban areas face many challenging issues; one of the most demanding is site selection. Strategic site selection issues are typically complex problems that require consideration of multiple alternatives (sites), multiple criteria and multiple decision-makers with conflicting interests, preferences and desires. In this perspective we propose a new decision making framework based on three areas of high importance: multi-agent systems, geographic information system and multiple-criteria decision analysis. These three tools are combined in a manner so that the shortcoming of one tool is complemented by the strength of the others. To assist the decision makers in selecting the compromise alternative from a number of feasible alternatives, the proposed decision support system will be enriched with a protocol of negotiation based on argumentation approach, which allows agents (decision makers) to exchange complex justification positions rather than just simple proposals, this property of argumentation protocols can lead to faster and beneficial agreements to the group.

Using positioning city hospitals, multi-criteria analysis method

The growth of cities is one of the most important global phenomena, which is occurring under the influence of environmental factors on the human, economic and political, and giving services to citizens and the city are of the priorities of the urban planners and managers. To accomplish this, a variety of techniques have been used both classical and modern. Since the 1970s, the use of quantitative methods in problems locating utilities increased and each of these methods in addition to the advantages and disadvantages in this field is used to study how the spatial distribution centers in Range, South of Tehran has been studied as the case the system uses a multi -criteria analysis. The issue of site selection, service, and service centers in the city is better. The purpose of this study is locating the appropriate municipal hospital in south of Tehran, is analytical and descriptive methods and the type of application. To achieve this objective the integration of GIS and hierarchical method (AHP) and GIS was used, the required layers, including the proximity to compatible land uses, access to the communication network, proximity to fire stations, population density, distance from the existing medical centers, away from the path, away from fuel stations, distance learning centers, land slope, proximity to the city center and close to green areas in GIS environment and then paired comparisons were performed by Expert choice software finally, by weighting the criteria and by combining layers of information, the most suitable place to build a city hospital was located in this area.

A bibliometric analysis on the solid waste-related research from 1982 to 2013 in Iran

A bibliometric analysis was used to assess the trend of solid waste-related publications produced by Iran and indexed in Scopus from 1982 to 2013. The study aims to analyze the distribution of languages, countries, institutes, journals, author keywords, authorship pattern and co-authorship relationships. The publication outputs showed an exponential trend (R 2 = 0.98) and increased by 45.3 % per year from 1982 to 2011. It was received with a decreasing trend to 44 papers at the end of 2013. Journal of Environmental Studies published the most papers. University of Tehran (25 %), Islamic Azad University (8.24 %), Tehran University of Medical Sciences (7.35 %) played active roles in the publication and Abduli MA was the most productive author (9.12 %) in this field. The English language was dominant language of all publications (88.24 %). The appearance of keywords namely “Heavy metals”, “landfill leachate” and “site selection” reveals the importance of release of heavy metals through landfill leachates and site selection issues in Iran. A downward trend in the number of publications is likely to be continued in future years. The highest cooperation was found among the capital universities in Iran and other institutions had a minor role in the production of articles. It is hoped that transferring the experiences by main universities and starting up teamwork activities may increase the number of researches in this field. It is expected that this study could be the basis for a better understanding of development of researches related to solid waste in Iran.

How good is good enough? Data requirements for reliable crop yield simulations and yield-gap analysis

Numerous studies have been published during the past two decades that use simulation models to assess crop yield gaps (quantified as the difference between potential and actual farm yields), impact of climate change on future crop yields, and land-use change. However, there is a wide range in quality and spatial and temporal scale and resolution of climate and soil data underpinning these studies, as well as widely differing assumptions about cropping-system context and crop model calibration. Here we present an explicit rationale and methodology for selecting data sources for simulating crop yields and estimating yield gaps at specific locations that can be applied across widely different levels of data availability and quality. The method consists of a tiered approach that identifies the most scientifically robust requirements for data availability and quality, as well as other, less rigorous options when data are not available or are of poor quality. Examples are given using this approach to estimate maize yield gaps in the state of Nebraska (USA), and at a national scale for Argentina and Kenya. These examples were selected to represent contrasting scenarios of data availability and quality for the variables used to estimate yield gaps. The goal of the proposed methods is to provide transparent, reproducible, and scientifically robust guidelines for estimating yield gaps; guidelines which are also relevant for simulating the impact of climate change and land-use change at local to global spatial scales. Likewise, the improved understanding of data requirements and alternatives for simulating crop yields and estimating yield gaps as described here can help identify the most critical “data gaps” and focus global efforts to fill them. A related paper (Van Bussel et al., 2015) examines issues of site selection to minimize data requirements and up-scaling from location-specific estimates to regional and national spatial scales.

Research on Modes of Cargo Ro-Ro, Drop and Pull Transport in Land-Sea Transportation Channel between Shandong and Liaoning

In order to accelerate national industrial upgrading of transportation and deepen the development of logistics industry, it is imperative to construct the land-sea transportation channel between Shandong and Liaoning provinces. Taking practical situations of the two places into account, the paper aims to investigate the application of M to N mode in the process of cargo roll on-roll off, drop and pull transport and then elaborate the site selection issue of drop and pull centers from the perspective of P-median model. Meanwhile, the paper proposes to adopt “south bridging-north rolling” concept to build a brand new transportation channel which combines the cross-sea bridge with ro-ro ferry concerning the natural conditions in Bohai Bay. Corresponding solution to each project will be put forward at last.