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Background: Iran is an earthquake-prone country, and a considerable rural population lives in earthquake-prone areas. With many worn-out areas, incompetent houses, and relatively underdeveloped rural areas, it is necessary to pay special attention to risk reduction and subsequent measures in these areas. Materials and Methods: Among the current methods, HAZUS is one of the most common methods in estimating potential losses in an earthquake. We used it to calculate the buildings' estimated losses in the earthquake based on the instructions. Because one of the main issues in disaster management is to choose locations for emergency or temporary settlement of population affected by the distracter, this research tries to carry this out based on the derived results from the damage using fuzzy Analytic Hierarchy Process (AHP). After reviewing the previous studies and the experts' opinions, the major and minor criteria affecting the selection of temporary settlement locations were identified. Results: Results suggested that using the damage rate of the studied buildings in the studied area and after choosing six priorities in the pilot village of Vaneshan, priority number 1 was chosen as the best option for temporary settlement in this village. Ultimately, the required items for the evacuees were determined by using the standards of supplying the essentials for the evacuees. Conclusion: Regarding the study area, the results of the damage analysis of the area show that the rate of damage with extensive and complete levels in the villages is very high, which leads to a large number of homeless people with the urgent need to provide adequate shelter. This endower requires a lot of money, and the relevant managers should already be thinking about finding financial resources for it. This issue is not only related to the study area and applies to the whole of Iran. [ABSTRACT FROM AUTHOR]

This paper investigates the Indoor Environmental Quality (IEQ) factors influencing occupant satisfaction in commercial buildings in Iran, contrasting the views of building experts (architects and engineers) with those of building occupants. Employing the fuzzy analytical hierarchy process (FAHP), this study focuses on the four primary IEQ factors: thermal comfort, indoor air quality, visual comfort, and acoustic comfort. The study aims to bridge the gap between expert evaluations and occupant perceptions of IEQ factors in commercial buildings in Iran. By examining the disparities in prioritising IEQ factors between these two groups, the study sheds light on the complexities of IEQ assessment and highlights the importance of considering diverse perspectives in optimising indoor environments. Our methodology includes a survey conducted among 30 building experts (15 architects and 15 building engineers) and 102 occupants, employing FAHP to derive the relative importance weights of each IEQ factor. The results highlight significant disparities between architects, engineers, and occupants in prioritising these factors. Architects emphasise visual comfort (42%), while engineers and occupants view thermal comfort (53% and 41%) as the most crucial factor for occupant satisfaction. The study underscores the complexity of IEQ in commercial buildings and the diverse perspectives influencing its assessment. It contributes to the broader discourse on optimising IEQ, emphasising the need for a comprehensive approach that encompasses both technical expertise and occupant experience. [ABSTRACT FROM AUTHOR]

This paper reports a realistic analysis of a region using Grounded Theory (GT) to provide a sustainable model for family farming systems based on the intercropping system in rural communities of Iran. Furthermore, the fuzzy analytic hierarchy process (FAHP) was applied to assign weights to the criteria and sub-criteria of intercropping and monocropping systems. According to the model, the main phenomenon was "sustainability in the family farming system based on intercropping". In this model, the causal factors were found to include behavioral and attitudinal motivators. Micro- and macro-factors were identified as the interfering factors in family farming systems based on intercropping. Social factors, economic components, and environmental potentials were the contextual factors of this system. Finally, the consequences included the conceptual development and evolution of sustainability, socioeconomic transformation, and ecological-environmental transformation. The results of FAHP showed that the environmental criterion was ranked the first among all criteria underpinning the sustainability of the intercropping system. [ABSTRACT FROM AUTHOR]

This paper reports a realistic analysis of a region using Grounded Theory (GT) to provide a sustainable model for family farming systems based on the intercropping system in rural communities of Iran. Furthermore, the fuzzy analytic hierarchy process (FAHP) was applied to assign weights to the criteria and sub-criteria of intercropping and monocropping systems. According to the model, the main phenomenon was "sustainability in the family farming system based on intercropping". In this model, the causal factors were found to include behavioral and attitudinal motivators. Micro- and macro-factors were identified as the interfering factors in family farming systems based on intercropping. Social factors, economic components, and environmental potentials were the contextual factors of this system. Finally, the consequences included the conceptual development and evolution of sustainability, socioeconomic transformation, and ecological-environmental transformation. The results of FAHP showed that the environmental criterion was ranked the first among all criteria underpinning the sustainability of the intercropping system. [ABSTRACT FROM AUTHOR]

In this paper, the numerical modeling of an indirect-expansion solar-assisted heat pump (IDX-SAHP) water heater system is proposed and the exergy-energy analyses and multiple-objective optimization (MOO) of the developed system are investigated. After the verification of the IDX-SAHP with the experimental results, the system performance is examined under the temperate climate of Iran throughout the year. Next, the sensitivity analysis (SA) of diverse variables comprising ambient temperature (T a) , solar intensity (I T) , water temperature at the condenser outlet (T W , o ) , compressor speed ( ω) , collector area (A cl) , thermal conductivity of the collector plate (k p) , number of the glass cover ( N gl) , tube diameter in the solar collector (D cl) , tube length in the condenser (L cond) , and absorber thickness of the collector plate (δ) is implemented via the one-parameter-at-a-time (OPAT) technique. Then, the influence of various factors such as T a , I T , A cl and ω on the exergy efficiency and exergy destruction of the IDX-SAHP system are studied. Besides, the single-objective optimizations (SOOs) and MOO processes are implemented through Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) to maximize the coefficient of performance (COP) and the collector efficiency (CE), individually and simultaneously. The results achieved by the SOOs depict that the design of IDX-SAHP as per the COP-based SOO offers a better system compared to the CE-based SOO. Furthermore, the optimal solutions obtained by the MOO are presented in the form of the Prato curve to depict the COP and CE interactions. Afterward, to achieve the final optimum layout of the system, the Analytic Hierarchy Process (AHP) technique as a robust multi-criteria decision analysis method (MCDM) is integrated with the MOO process through MATLAB programming language. The optimization results demonstrate that the MOO process gives better performance compared to the SOO process in such a way that although the CE of the maximized IDX-SAHP reduces a little from 52 to 47 % , its COP is enhanced greatly from 3 to 7 , resulting in reduction of the total working hour of the system up to 282 hours compared to the initial system, and consequently, the overall power use of the maximized system largely reduces. This investigation clarifies the importance of exergy-energy analyses, SA, MOO, and MCDM during the IDX-SAHP design to increase efficiency and decrease the power use of the system by opting the most appropriate design parameters of the system. [ABSTRACT FROM AUTHOR]

Mining activities are liable to injuries and different types of diseases. The occurrence of an accident threatens safety in dimension stone mines. Therefore, the safety risk assessment in such mines is an important issue that needs special consideration. In this paper, the safety risk of incidents in dimension stone mines in Iran is evaluated using the fuzzy inference system. The fuzzy analytical hierarchy process is used to identify the importance degree of each incidence and then, the overall risk priority number is calculated based on the fuzzy inference process. The results of this study show that vehicle traffic and wire rupture are the most hazardous incidents. [ABSTRACT FROM AUTHOR]

Hazards in underground coal mines create an unsafe working environment for workers and equipment. This paper aims to analyze the safety risk in underground coal mining using an improved Failure Mode and Effect Analysis (FMEA) method. To achieve this, the causes of the main events that threaten the safety of the working environment were identified and discussed in a case study; Parvadeh Tabas coal mine, Iran. The Analytical Hierarchy Process (AHP) was applied to calculate the importance degree of each hazard. Then, the FMEA approach under the fuzzy environment was used for the safety risk analysis. Regarding the results of this study, the outburst-related hazards, failure to provide sufficient compressed air, and the electrical locomotive-related hazards have the highest level of safety risk. In this concept, it is possible to identify the leading causes of accidents and propose practical solutions to improve the safety conditions of the mine working places. [ABSTRACT FROM AUTHOR]

This paper presents a novel method for the development of an optimal water supply plan showcased using data from the Gamasiab basin, located in Kermanshah province, Iran, concerning new dams that are being constructed in this semi‐arid region. In this paper, a new group multi‐criteria decision‐making (MCDM) plan is proposed by combining two MCDM methods based on the fuzzy Delphi and fuzzy ELECTRE III methods that convert the experts' opinions to triangular fuzzy numbers based on the level of uncertainty associated with various quantitative and qualitative criteria. Considering the opinions of four non‐stakeholder experts and data analysis using the fuzzy Delphi method, the criteria were evaluated. Then, by analysing the results using the fuzzy ELECTRE III method, the final ranking of scenarios is obtained. A sensitivity analysis was conducted to assess the effect of uncertainty on the performance of the decision‐making system in scenarios ranking. The total expense, flood control, reservoir capacity and diversion and water transfer played a significant role in selecting the optimal scenario. Additionally, a hydrologic model was developed to evaluate the performance of the optimal scenario in terms of qualitative criteria. The data indicated that there was a good agreement between the results obtained from the hydrological model and the scenario ranking by the employed method. Altogether, a comparison of the proposed method with other MCDM methods, including fuzzy analytic hierarchy process and fuzzy technique for order preference by simulation of ideal solution, indicated that the results of the employed method matched more closely to the local experts' opinion. [ABSTRACT FROM AUTHOR]

This research is aimed at comparing the performance of a proposed data-driven VIKOR method with its knowledge-driven version for porphyry copper prospectivity modeling in the Sardouyeh district, Kerman province, SE Iran. Sixteen exploratory layers from various sources were first nominated for this purpose. These layers were provided from the following sources: (1) multi-element geochemical signatures derived from principal component analysis (PCA); (2) distribution of geophysical footprints derived from aeromagnetic and potassium radioelement surveys; (3) proximity to ore host rocks and tectonic controls; and (4) proximity to hydrothermal alterations. For better comprehension of exploration layers, their values were transferred to the same range [0–1] using fuzzy logic. For predictive modeling of porphyry-type copper mineralization, an improved data-driven VIKOR model was introduced in this paper that its main foundation is based on the calculation of criteria and their relevant classes weights in a data-driven way using prediction-area (P-A) plots and normalized density index (N d), respectively. This methodology was applied twice: once on all exploratory layers and again only on efficient evidence layers. In order to compare and evaluate the performance of the novel methodology introduced for predicting high-favorable areas associated with Cu-porphyry deposits, on the basis of expert opinion and an Analytic hierarchy process (AHP) approach, the AHP-VIKOR procedure was implemented as a knowledge-driven method. A success-rate curve was employed to accurately compare the performance of three models, quantitatively. The findings reveal that the improved data-driven VIKOR approach using efficient evidence layers covered 80 % of Cu occurrences in only 6 % of the total area of the region, which led to much more precise and high-quality outcomes. Moreover, it provides more effective performance to be employed for more detailed exploration programs in this study area and similar studies in other regions. • Discovery of mineral reserves plays a major role in economy and industry. • Knowledge-based and data-based methods are used to explore mineral deposits. • Unlike knowledge-based methods, data-driven methods reduce uncertainty. • Developing a novel data-based VIKOR algorithm is useful in Cu prospectivity mapping. • Using data-based VIKOR is more accurate with involvement of only efficient criteria. [ABSTRACT FROM AUTHOR]

Despite the large amount of information, including books, articles and pristine images of geotourism, there exists no comprehensive study on the collection and classification of them in Iran yet. In this research, for the modelling of geosite watersheds, 1000 articles were surveyed through library research and the models with the highest frequency of use were identified and analysed among a statistical sample of 451 local papers using the Meta-Analysis method, and then the most efficient ones were identified using Delphi and Analytic Hierarchy Process (AHP) methods. The results of this study showed that while the strengths, weaknesses, opportunities and threats (SWOT), Pralong, Reynard, AHP and Pereira models are in the first to fifth-ranked models with the highest frequency, however, Pralong, SWOT, Reynard, Perira and Comanescu models were considered as the most efficient ones in geosite modelling in Iran. [ABSTRACT FROM AUTHOR]

The dominance of conventional fuels in Iran and therefore increasing concerns about its side effects (both environmental issues and economical) has required the Government and policymakers to switch to the adoption of renewable technologies. However, facing some obstacles has lowered the adoption rate of these technologies. Therefore, by applying Analytical Hierarchy Process (AHP) method, this paper tends to identify and rank the main barriers to the development of the three alternatives in Iran, named solar PV, wind turbines, and biomass. From the literature review and experts' viewpoints, thirteen barriers have been identified and accordingly have been grouped into five dimensions, called 1. Economic & financial, 2. Social, cultural, & behavioural, 3. Political & regulatory, 4. Technical, and 5. Institutional. The sensitivity analysis has been conducted to check the stability of the priority ranking of the stated alternatives. The results showed that there are fewer limitations to the development of solar PV, followed by wind turbines and biomass. Therefore, to formulate and frame appropriate policies and strategies to foster the adoption of renewable energy technologies, at the first step, the Government and policymakers must pay more attention to overcome the hindrance to the expansion of solar PV. [ABSTRACT FROM AUTHOR]

With an increasing number of different materials, choosing the best one has become an arduous task. The vast domain of alternatives and decision criteria has led to the complexity of decision making in the conceptual phase for designers. On the other hand, due to the importance of environmental and energy concerns, considering the sustainability principles through the decision process is significantly important. Although sustainable material selection as a strategy leads to some general and main assessment criteria, identification of sub-criteria not only depends on general criteria but also pertains to the specific type of elements in buildings. Interior walls are one of those elements in construction with a complex decision making process due to their great variety of types and features. This paper aims to provide a sustainable multi-criteria decision making framework for choosing the proper interior walls in buildings. A qualitative research method using literature review, unstructured interviews and questionnaires was adopted to achieve the aims of this research. The initial data, including the criteria and sub-criteria, were collected through literature review. A framework consisting of four main components related to environmental, financial, social and technical aspects was finally developed and validated through unstructured interviews held with 23 experts in the construction industry in Iran. By dividing the main criteria into sub-criteria, in total, 23 sub-criteria were identified; to calculate their weight, questionnaires were distributed among 143 experts in the construction industry in Tehran and the analytic hierarchy process method was applied. High-rise residential buildings in Tehran were selected as a case to apply the framework, and finally the results are discussed. [ABSTRACT FROM AUTHOR]

Unsafe driving behavior and hazardous environmental conditions lead to traffic crashes and injuries. The annual rate of road crashes in Iran is twenty times higher than the world's average. Motorcycle crashes have higher fatality rates than other motor vehicle crashes, and they exert psychological pressure on the communities and have adverse economic consequences for the societies. This paper analyzes Tehran's motorcycle crash data and investigates the effective underlying factors. Seven strategies were presented and prioritized to reduce the number and severity of motorcycle crashes. The fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) combined with the Analytical Hierarchy Process (AHP) was used to analyze and prioritize the recommended strategies. The combination of TOPSIS, AHP, and fuzzy theory improves the prioritization reliability and yields robust inferences. Based on the conducted analysis, it was concluded that the induction of social and cultural values, stimulating the sense of citizenship, and providing professional training programs have the highest priorities among the other strategies for reducing motorcycle-related fatalities and injuries. [ABSTRACT FROM AUTHOR]

The mineral exploration sequence contains field planning, data processing and assessment of results for further decision making. These need many decisions of critical importance for detecting new prospecting zones and the choice of the methodology to be applied in such areas. In this paper various exploration layers were synthesised by Additive Ratio Assessment (ARAS) and Weighted Aggregated Sum Product Assessment (WASPAS) models to generate an optimal Mineral Prospectivity Map (MPM) of Cu-Au mineralisation in the Sonajil area, NW of Iran. Here the knowledge-driven method was adopted using the Multi-Criteria Decision Making (MCDM) approach for preparation of MPM. For this purpose, the Geographic Information System (GIS) was utilised by considering geochemical, alterations, tectonic, remote sensing and lithological evidential layers. Initially, the separation of populations for exploration layers was performed by fractal method, and the layers were classified using the results of the threshold limit. Then the analytic hierarchy process (AHP) technique is implemented to weigh the evidential layers. Accordingly, the decision matrix was formed using the values assigned to the pixels of these maps and the weights obtained by the AHP method, which was used in both the ARAS and WASPAS models to acquire the final MPM. The resulting map was cross-validated by the results of the petrography study of the samples taken from the mineralised zones indicated by MPM, thereby presenting the efficiency of the proposed approach as a well-established integrated model, sufficiently powerful to distinguish precise promising zones in centre and northeast of the area, with a successful extension of the mineralisation in the adjoining. [ABSTRACT FROM AUTHOR]

We have proposed a data-driven method for spatio-temporal analysis of car crashes based on the Multi Criteria Decision Making (MCDM) procedure in the Zanjan city, NW Iran which are recorded in the period 2019–2020. A combination of Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used in this paper to accurately identify the spatio-temporal interactions exist in car crashes. A data-driven AHP-TOPSIS procedure is arranged based on assigning proper weights to the time series related to the peak of accidents. On the other hand, for spatial analysis, the Kernel Density Estimation method was used to create the continuous-value maps of different traffic accidents and then classified using Natural Breaks Classifier. In fact, the proposed methodology can be used to identify car crash hotspots by considering spatio-temporal interactions as well as addressing exaggerated weightings arising from knowledge-driven modeling. By using the spatio-temporal interaction maps in which the location and time of crashes are considered, simultaneously, it is possible to provide a new scientific strategy for identifying car crash hotspots which can lead to better traffic management, improved allocation of resources, and enhanced prevention regulations. • Proposing a method for analyzing car crashes based on spatio-temporal interactions. • Based on MCDM, a data-driven method used for spatio-temporal analysis. • Developing an AHP-TOPSIS hybrid model for car crash spatio-temporal interaction. • Using Kernel Density Estimation to create the continuous-value maps of car crashes. • Providing a car crash hotspot map including both location and time simultaneously. [ABSTRACT FROM AUTHOR]

Analytical hierarchy process (AHP) is among the most widely used multi-criteria decision-making (MCDM) methods that have been employed by researchers in various scientific areas all over the world to find the most appropriate solutions for complex and multivariable problems. Despite the popularity of this method, there is no scientometric study on AHP applications in the literature. To fill this gap, the present study aims to present a scientometric analysis on the use of AHP for various applications, in general, and particularly for making the best decisions when dealing with urban management. Current scientific trends in this area were also identified and presented through an in-depth analysis of the findings regarding contributing countries, journals and authors. In addition, the main keywords introduced to the field and the existing categories were explored and identified. Results demonstrated that out of the 37,000 scientific works (including journal articles, proceedings, books, etc.) published so far on the employment of AHP in various fields, only 7% contributed to the urban affair management issues, whilst China and Iran hold the highest share. Results also indicated that AHP has been efficiently combined with Geographic Information System (GIS) to address the scientific needs in this area. This paper also provides recommendations for relevant future studies. [ABSTRACT FROM AUTHOR]

Water reuse allocation is one of the major challenges in water resource management which requires the assessment of water reuse alternatives, especially in regions with limitation in water resources, arid climates, population growth and increasing water demand. Considering the complexity of the problem, water reuse allocation by using conventional methods for maximizing benefits, minimizing cost and environmental risks, cannot guarantee optimal allocation. In this paper, Analytic Hierarchy Process (AHP) which can be combined with Goal Programming (GP) by considering the Leopold matrix for carrying-out the Environmental Impact Assessment (EIA) is used for sustainable water reuse allocation for multiple stakeholders in Najafabad as a case study. The results show that the developed mathematical model with combination of quantitative evaluation and optimization can be considered as an effective and flexible tool for creating better guidelines to adapt the requirements of various stakeholders for better allocation of recycled water. Finally, based on sensitivity analysis in AHP, a What-If analysis in GP is performed to the robustness of the final results of water reuse allocation. [ABSTRACT FROM AUTHOR]

As a service-oriented supply chain, blood supply chain management deals with a human-to-human network involved with a number of direct challenges such as irregularity in both blood supply and demand as well as multiplicity of blood products, their respective lifetimes and perishability. Besides, facing risks originating from natural disasters or man-made incidents such as labor strikes, economic problems, and so on, and from uncertainty embedded in the input data is also a real highlight in designing and managing a blood supply chain network. This paper addresses an enhanced perspective incorporating a two-phase preemptive policy by which the disruption risk is diminished through a hybrid technique using the fuzzy analytic hierarchy process and grey rational analysis for determining supplementary blood facilities, to cooperate in production process and decrease interruptions. Furthermore, a p-robust formulation is presented to control the network reliability under disruption scenarios at minimum cost. To protect the network against the uncertainty, a consolidated approach based on a recently developed fuzzy measure is extended. We also examine the validity and practicality of the proposed model and its solution perspective along with the reliability of the network by a real case of Iran. It is worth nothing that the problems in the case of disasters in which the impact of the two risk streams will be felt most keenly, could benefit from the proposed procedure advantages since it develops a proactive and controlling approach which can be extensively applicable in disastrous situation. [ABSTRACT FROM AUTHOR]

Solar energy plays a crucial and high-priority role in protecting and maintaining our future environment. One of the most important and outstanding factor in building a power plant is how to choose the appropriate and suitable site for solar power plants. The purpose of this research is to investigate the most felicitous locations in order to establish the photovoltaic power stations in Iran.it is highly recommended to closely consider the economical and geographical conditions. The required data were mostly obtained from satellite images and ground measurements. The principle in this paper forms some effective factors made up of in site selection and developed some guidelines about how to divide them into four categories including the value of solar radiation on earth's surface, the economic features, the technical factors and geographical considerations. It is extremely necessary to recognize the need to closely examine an important issue that these factors were analyzed and weighted by Analytical Hierarchy Process (AHP) and then the potential map was extracted. An understanding and appreciation of results represent appropriate locations namely Fars and Sistan and Baluchistan provinces which have higher potential to build Photovoltaic power plants. Ultimately, through research, it has been developed a model and map with maximum efficiency for gaining a deeper understanding of the most suitable location for the fixed panel power plant which was obtained. [ABSTRACT FROM AUTHOR]

The optimal siting of wind farms is a multi-attribute problem, and different objectives and constraints like economic, environmental, social, and technical should be taken into account. The widely-used category of site selection methods, multi-criteria decision making (MCDM), suffers from local scoring despite its numerous advantages. In this paper, support vector regression (SVR) is implemented to add the global scoring capability to MCDM by using a global-scale span of decision criteria. Here, the weighting of the decision criteria is obtained by the analytic hierarchy process (AHP), and then an SVR is utilized to appoint a score to any candidate site location. The proposed procedure has been used to study potential wind sites in Iran. In this regard, the study was conducted through three scenarios based on the natural and artificial potential of candidate sites. This study reveals that there are several vast areas, especially in eastern Iran, having high wind power density and flat terrain that are ready to be utilized as an endless source of clean energy provided that proper investment is made in power transmission lines and road networks. [Display omitted] [ABSTRACT FROM AUTHOR]

Selecting a suitable site is a critical step in wind energy projects. In this regard, using appropriate decision criteria plays a significant role. Turbulence intensity is one of the main characteristics of airflow that affects the power production and lifespan of wind turbines. Therefore, it is considered as a wind site selection criterion in this paper. The present paper formulates the effect of turbulence on both power production and lifespan of wind turbines via an equivalent wind power density (WPD eq) function, to use it in the wind site selection process. To implement the proposed methodology, 88 wind sites in Iran have been studied. The results reveal the significant effect of turbulence on the site selection process as some sites have changed their rank up to 8 grades considering turbulence intensity in the siting process. To consider the turbulence intensity as an independent criterion to use it in multi-criteria decision-making methods, its relative importance (weight) have to be calculated. Sensitivity analysis shows that, on average, the relative importance of turbulence intensity over wind power density can be approximated as 1/5. Researchers can quickly consider turbulence intensity in siting process incorporating its weight in the pairwise comparison matrix of multi-criteria decision–making. • The effect of turbulence intensity on wind site selection was studied systematically. • Studying 88 sites shows the significant impact of turbulence on wind site selection. • Relative importance of turbulence criterion was estimated using sensitivity analysis. [ABSTRACT FROM AUTHOR]

Evaluation of suitable sites for locating a large extractive industrial unit can be considered as a multi-criteria decision-making problem. Such a complicated process often requires considering the conflicting tangible and intangible criteria. This paper aims to propose a combination of a Delphi-analytical hierarchy process approach and geographical information system methodology in order to find the optimum sites for the large extractive industrial units in Iran. To this end, the most influential criteria and sub-criteria were firstly identified and weighted using Delphi method and analytical hierarchy process, respectively. Then, in order to specify the suitable sites for establishing a large extractive industrial unit in Iran, the results obtained from analytical hierarchy process were integrated into the weighted index overlay method in the geographical information system environment. The combination of Delphi and analytical hierarchy process with geographical information system revealed an acceptable performance for the identification and weighting of the effective criteria and the selection of the most suitable large extractive industrial unit sites in Iran. [ABSTRACT FROM AUTHOR]

Today, using only one geophysical layer creates a large percentage of errors in the mineral exploration field. For this reason, the integration of different exploration layers with the geophysical layer for mineral exploration is suggested. The fuzzy analytical hierarchy processes (AHP) method is a manner of mineral prospectivity mapping (MPM) that is generally used for mineral exploration. This method has been applied for multi-criteria decision-making problems. In this paper, fuzzy AHP and geospatial information system (GIS) were used to generate a prospectivity model for Cuporphyry mineralization on the basis of a conceptual model and geo-evidence layers derived via geological, geochemical, and geophysical data in the Fordo area, central Iran. Fuzzy AHP was utilized to determine the weights belonging to each criterion. Three geoscientists' knowledge of exploration of Cu-porphyry mineralization has been applied to assign weights to evidence layers in fuzzy the AHP MPM method. After assigning normalized weights to all evidential layers, a fuzzy operator was applied to integrate weighted evidence layers. The results demonstrate the acceptable outcomes for Cu-porphyry exploration. For further evaluation of the prospectivity model, C-A fractal model was used for the MPM. Finally, the C-A prospectivity map was confirmed by checking three target areas in the field. [ABSTRACT FROM AUTHOR]

Geographic Information System (GIS) are very useful tools for managing, checking, and organizing spatial information from many sources and of many types in thematic layers. In this paper, using GIS, we describe and compare different models for the estimation of porphyry copper potential maps in Ahar-Arasbaran zone, north-western Iran. Final potential mapping of the study area was assessed according to the advantages and disadvantages of each method and a combination of them. The results demonstrate that the Analytic Hierarchy Process (AHP) method provides the best output with the lowest potential area and the highest point validation coverage, and highlights a new potential area of porphyry copper mineralization confirmed by field check. [ABSTRACT FROM AUTHOR]

Globally, most industrial parks that have not gone through a proper site selection process have been neglected or underutilised and such active sites tend to burn a lot of fuels and generate greenhouse gases. Technology must be used to conduct on-site investigations of the spatial and non-spatial factors of industrial parks, especially the emerging Eco-Industrial Park (EIP). The paper seeks to appraise the global application, capability and acceptability of Geographic Information System (GIS) and Multi-Criteria Decision-Making (MCDM) tools in the EIP sites selection and planning. Also, to identify the benefits of mixing MCDM tools when integrating with GIS. There have been some reviews on the use of GIS and MCDM methods, but so far, there is none on the role of GIS and MCDM methods in EIP site selection. Geospatial and MCDM tools can be used to carefully select EIP sites, where materials and energy can be shared to achieve cleaner production, reduce environmental pollution and promote sustainable development. To understand the usage of these tools and their role in the EIP site selection process, a critical review of twenty-two papers published from 2007 to 2020 indexed by Google Scholar, Springer, IEEE Xplore and Web of Science have been developed for the first time. The articles are classified based on country/region, journal of publication, year and citations of publication, the authors and technologies applied. The results show that most studies on EIP site selection come from Iran and China. The Journal of Environmental Monitoring and Assessment has the highest number of articles published at 28%. The highest number of articles was published in 2014 with 312 citations. GIS and Analytic Hierarchy Process (AHP) topped the technologies used, accounting for 42% and 24% respectively, and hybrid tools 34%. As categorised by criteria content, there was an overlap of criteria in most journals. Though, water bodies, utilities, infrastructure, and natural characteristics were prominent. Renewable energy resources were not given attention by most researchers, and risk assessment was absent from the site selection literature. A blend of traditional MCDM tools constitutes the state-of-the-art tools, and when these are combined with GIS in EIP site surveys, they execute to obtain actual results. Future EIP site selection that is integrated with risk assessment is envisioned to be industry 4.0 (4IR)-driven through a combination of GIS and artificial intelligence, and the recently developed MCDM hybrid modules. [Display omitted] • Poor site selection has led to industrial park being neglected or underutilised. • Abandoned/underutilised active industrial parks can burn fuels to cause GHG. • First time of critical review of role of GIS and MCDM tools in EIP site selection. • GIS and AHP currently mainly used for large-scale EIP site criteria selection. • EIP site choice risk study using GIS, AI and MCDM hybrid can sustain industry 4.0 [ABSTRACT FROM AUTHOR]

This paper presents the development of a spatial model for the allocation of the Urban Search and Rescue (USAR) operation by computing the priority index of damaged areas (PI-USAR model). The relevant prioritization criteria were identified through a literature review and interviews with 30 disaster managers. The relative importance of these criteria was computed as weights using an analytic hierarchy process (AHP) method; the criteria were combined based on AHP rules and spatial multi-criteria decision-making analysis in geographic information system (GIS). The PI-USAR model was applied in the case study area of the Bam city in Iran and a priority map was produced indicating four highly prioritized areas. The model was validated by comparing the obtained priority map with the actual priority map (APM) using fuzzy inference system and relative operating characteristic methods. The result suggested a good fit between the APM and the model's output. Sensitivity analyses were performed using the map removal and the single parameter methods. With the uncertainties and complexities that are inherent to the spatial data, spatial modelling and the earthquake phenomenon itself, the PI-USAR model offers some utility to disaster managers in understanding the significance of each criterion in the decision-making process and in identifying the highly prioritized areas for the allocation of USAR operations. However, its utility is best exploited in conjunction with other complementary sources of field data based on the immediate post-disaster situation. [ABSTRACT FROM PUBLISHER]

Enterprise Resource Planning (ERP) plays an important role in today's enterprise management and is beginning to be the backbone of organizations and started working on the next-phase in the enterprise system life-cycle, referred to as ERPII . Implementation of ERPII projects takes a considerable time and resources from the organization. Therefore, it is essential that critical success factors (CSFs) of ERPII implementation are identified and Prioritized. According to what was said, the main purpose of this paper is: Identification and Prioritization of CSFs in the ERPII implementation in Iran. According to this objective, The authors initially use a related topic of CSFs in ERPII systems implementation, which aims at identifying and investigating factors that result in more successful ERPII systems implementation that generate higher levels of value for organizations. Then this factors will be prioritized by Analytic Hierarchy Process (AHP). [ABSTRACT FROM AUTHOR]

Given the growing competition in domestic and international agricultural product markets, choosing a business strategy compatible with requirements of marketing resources can guide agro-food firms to maintain and enhance competitive advantages. However, this is not as simple as it seems because the decision-making criteria expressed in a fuzzy manner and the relationship between them can be hierarchical or network-based. Therefore, the main goal of this study was to select the most suitable business strategy and to prioritize marketing resources for one of the major agro-food firms in Iran. To ensure the robustness of the results, both fuzzy analytic hierarchy process (AHP) and fuzzy analytic network process (ANP) were applied to prioritize business strategies and marketing resources. The results of both methods revealed that the differentiation strategy had the highest priority in terms of the experts' viewpoints. The results also showed that managerial and customer relationship capabilities were the most important criteria in selecting the differentiation strategy. According to the findings of the study, for the successful implementation of the differentiation strategy, company managers are recommended to take the following three main elements into huge consideration: financial conditions, paying attention to customer's needs and requirements, and the introduction of new products and services. [ABSTRACT FROM AUTHOR]

One of the major strengths of a GIS is the ability to integrate and combine multiple layers of geoscience data for producing mineral potential maps showing favorable areas for mineral exploration. Once the data is prepared properly, the GIS, jointly with other statistical and geostatistical software packages, can be used to manipulate and visualize the data in order to produce a mineral prospectivity map. Many spatial modeling techniques can be employed to produce mineral potential maps. This paper demonstrates a technique to define favorable areas for REE mineralization with AHP technique using geological, geochemical, geophysical, alteration and faults density spatial data in the Kerman-Kashmar Tectonic Zone of central Iran. The AHP is a powerful and flexible multi-criteria decision-making tool for dealing with complex problems where both qualitative and quantitative aspects need to be considered. This approach is knowledgedriven method and can be applied in other areas for conventional use in mineral exploration. [ABSTRACT FROM AUTHOR]

Abstract: Mobile cellular telecommunication success in target markets first requires ranking the customer’s expectations and then prioritizing the engineering characteristics (ECs) to meet the expectations. In this paper, two prioritization models based on quality function deployment (QFD) are developed to rank the strategic actions (SAs), or the ECs of Iran mobile cellular telecommunication. QFD is a widely used customer-driven tool for which the success of its applications may be the result of some of its benefits, such as greater customer focus. It uses a matrix called House of Quality (HOQ) to translate Customer Attributes (CAs) into ECs. However, due to the high degree of subjectivity in constructing the HOQ, the application of fuzzy logic provides an efficient tool to handle the subjective assessments. On the other hand, taking into consideration the gap between the current state and the positive ideal state for each CA, TOPSIS is used to rank CAs in a first model. In addition, in a second model, using the analytic hierarchy process (AHP), more criteria are taken into consideration in ranking CAs. Also, a fuzzy utility factor, B j , is used to rank SAs in both models. Both presented models have the ability to capture the vagueness of human thinking style, and let customer oriented organizations, such as MCI, derive benefits from the voice of the customer (VOC) in a more expressive way. [ABSTRACT FROM AUTHOR]

Unplanned pumping of groundwater in the past two decades has caused many regional problems and tensions, leading to seawater intrusion into coastal aquifers. The main objective of this paper is the use of a Multi-Criteria Decision-Making (MCDM) approach combining with numerical simulation for reducing seawater intrusion in the Tajan coastal aquifer located on the southern seashores of the Caspian Sea, Iran, taking into account economic, social, and environmental issues. The MODFLOW code was used to simulate the groundwater flow. MT3DMS and SEAWAT codes were used to simulate the solute transport and seawater intrusion. A 10-year period from 2010 to 2020 was simulated for evaluating the current conditions and forecasting the future conditions of the aquifer. The results indicated an increase in the extent of seawater intrusion. To assess the proposed eleven curative solutions, the economic, social, and environmental criteria such as efficiency of applying of curative solutions in improvement of the aquifer's water level and efficiency of applying of curative solutions on reduction in the extent of the seawater intrusion were weighted using the Analytic Hierarchy Process (AHP) method. The results of the AHP method showed that the criterion of efficiency of applying of curative solutions in improvement of the aquifer's water level with the weight of 0.311 was the most important one. Three multi-criteria decision making methods namely, Simple Additive Weighting (SAW), Technique for Order Performance by Similarity (TOPSIS), and VIse Kriterijumska Optimizacija kompromisno Resenje (VIKOR) were utilized to select the best curative solution. The solution of 10% reduction of pumping rate and the construction of Gelvard dam in the SAW and TOPSIS methods and the solution of 3% reduction of pumping rate and the construction of Gelvard dam in the VIKOR method ranked first. Combined techniques namely, the Rank Average Method, Borda's Method, and Copeland's Method were used to develop a consensus on prioritizing curative solutions for the Tajan Aquifer. The results of these techniques showed that the solution of 10% reduction in pumping rate along with the construction of the Gelvard dam was the best. The results of simulating this solution demonstrated a 1.91 m improvement in the groundwater level of the aquifer in the MODFLOW code and a 361.5-m recede in seawater intrusion length along the coast in the SEAWAT code. • Saltwater intrusion from the sea or saline lakes into freshwater aquifers degrades the potable quality of these resources. • Appling MODFLOW, MT3DMS, and SEAWAT to simulate groundwater flow, solute transport, and seawater intrusion. • Proposing 11 curative solutions to control seawater intrusion in Tajan aquifer located in Iran. • Using MCDM methods to select the best curative solutions. [ABSTRACT FROM AUTHOR]

• A novel healthcare waste location-routing problem is developed with a new perspective in healthcare logistics networks. • A stochastic essence for the emission of contamination is considered. • The management of medical wastes in Coronavirus Disease 2019 is focused. • A real case study is modeled to manage the logistics of infectious and non-infectious healthcare wastes. • A Multi-Objective Water-Flow like Algorithm with novel operators is developed and compared with the others. This paper presents a novel healthcare waste location-routing problem by concentrating on a new perspective in healthcare logistics networks. In this problem, there are healthcare, treatment, and disposal centers. Locations of healthcare centers are known, however, it is required to select appropriate locations for treatment, recycling, and disposal centers. Healthcare wastes are divided into infectious and non-infectious wastes. Since a great volume of healthcare wastes are infectious, the emission of contamination can have obnoxious impacts on the environment. The proposed problem considers a stochastic essence for the emission of contamination which depends on the transferring times. In this respect, transferring times between healthcare and treatment centers have been considered as normal random variables. As transferring time increases, it is more likely for the contamination to spread. Having visited a treatment center, infectious wastes are sterilized and they will no longer be harmful to the environment. This research develops a bi-objective mixed-integer mathematical formulation to tackle this problem. The objectives of this model are minimization of total costs and emission of contamination, simultaneously. Complexity of the proposed problem led the researchers to another contribution. This study also develops a Multi-Objective Water-Flow like Algorithm (MOWFA), which is a meta -heuristic, to solve the problem. This algorithm uses a procedure based on the Analytical Hierarchy Process (AHP) to rank the non-dominated solutions in the archive set. By means of a developed mating operator, the MOWFA utilizes the best ranked solutions of the archive in order to obtain high quality offspring. Two neighborhood operators have been designed for the MOWFA as the local search methods. Extensive computational experiments have been conducted to evaluate the effectiveness of the MOWFA on several test problems compared with other meta -heuristics, namely the Multi-Objective Imperialist Competitive Algorithm (MOICA) and Multi-Objective Simulated Annealing (MOSA). These experiments also include a real healthcare waste logistic network in Iran. The computational experiments demonstrate that our proposed algorithm prevails these algorithms in terms of some well-known performance evaluation measures. [ABSTRACT FROM AUTHOR]