Analytic Hierarchy Process Technique Research Articles

An optimal organizational excellence model for the public sector

PurposeCurrent models of organizational excellence are appropriate for the private organizations. It is evident that if an appropriate model is not adopted, the process of excellence in the organizations fails and some dimensions of the organization get affected by unpredictable damages. This research aims to identify an appropriate excellence model for public organizations.Design/methodology/approachFirst, a comprehensive literature review was conducted to identify the excellence criteria and models. Second, the models were through an expert-oriented questionnaire, analyzed by the analytical hierarchy process (AHP) technique. Participants were experts in the two domains of excellence models and public sector management. A sample of 15 experts was selected using purposive sampling. In order to emphasize on reliability, 10 questionnaires were adopted for analysis.FindingsThe findings showed that the European Foundation for Quality Management (EFQM) model is the most appropriate model for excellence measurement in the public organizations based on the five selected indices.Originality/valueThe identification of a model for measuring organizational excellence for public sector can significantly contribute to existing literature on excellence measurement.

On potential strategic framework for green supply chain management in the energy sector using [formula omitted]-rung picture fuzzy AHP & WASPAS decision-making model

The present communication deals with addressing the problem of handling the uncertainties in the process of green supply chain management system through an integrated approach that takes the information in the form of q-rung picture fuzzy sets and quantitatively blends it into the decision-making techniques of Analytic Hierarchy Process (AHP) and Weighted Aggregated Sum Product Assessment (WASPAS). The proposed model has been implemented in stage-wise form for outlining the potential strategic plans for green supply chain management in the energy sector. At every phase of the study, the detailed analysis has been presented in an interlinked manner for solving the underlying problem of decision-making. A brief sensitivity analysis and comparative study of the potential strategic plans with respect to the deterministic parameters have been performed for better understanding, consistency, and reliability. The findings of the propositions illustrate that while making prioritization for potential strategic plans, concentrating on utilizing customer relationship management to meet the needs of the customers is more prominent than examining the procedure for developing new services and products.

Comparative analysis of certainty factor and analytic hierarchy process for landslide susceptibility zonation in parts of Solan, Himachal Pradesh, India

The state of Himachal Pradesh in India is one of the most important hotspots when it comes to landslides; and Kandaghat, a tehsil in the Solan district of Himachal Pradesh having religious and tourism importance, is substantially affected by frequent landslides causing road blocking. In the present study, the analytic hierarchy process (AHP) and certainty factor (CF) techniques, which form part of the geographic information system (GIS)-based landslide susceptibility models, were used to prepare a landslide susceptibility map for the Kandaghat region, for which, as a preliminary step, an inventory of 214 live landslides was prepared from the Bhukosh data directory. The landslide inventory was cross-verified on the Google Earth platform. About nine landslide causative factors (slope, curvature, aspect, soil, rainfall, land use–land cover, lithology, drainage density and lineament density) were considered for the study area, and against the backdrop of these, the corresponding thematic maps were prepared and used in turn for the preparation of the final landslide susceptibility map. Based on the two mentioned techniques, the thematic maps were assigned weights according to their prominence and dynamic processes in the study area. The model performance for each method was evaluated using the area under the curve (AUC), and the accuracies for the AHP and CF were ascertained as, respectively, 81% and 85.6%. The Himalayan terrains are significantly prone to landslides, and this study outlines the characteristics of one of the important Himalayan towns in terms of vulnerability for landslides, together with providing its classification in terms of slope deformation susceptibility; this procedure can help direct attention towards areas needing to be classified under high to very high landslide susceptibility zones.

Developing an extended producer responsibility system for solid waste management in Jordan using multi-criteria decision-making approach.

To move from a traditional end of pipe approach into a more sustainable solid waste management system, the Jordanian Government has recently passed a set of new regulations The National Solid Waste Management Strategy has put a road map to encourage circular economy practices. One of the considered policy instruments is the adoption of the extended producer responsibility (EPR). The current study aimed to adopt a multi-criteria decision-making method to select the most convenient EPR structure within the Jordanian context. The study used analytical hierarchy process (AHP) and fuzzy AHP (FAHP) techniques to select the suitable type of producer responsibility organization (PRO) structure. A four-level hierarchy model was constructed with 4 criteria, 10 sub-criteria and 3 PRO alternatives. The analysis revealed that the legal and administrative criteria is the most important one (0.47) followed by environmental criteria (0.22), whereas the least important ones were socio-economic (0.17) and technical criteria (0.13). The most preferable PRO alternative was found to be PRO with profit. There were slight differences between all weight values under AHP and FAHP. Despite the availability of several laws, there is a need to develop the legal and administrative framework to enable the adoption of EPR in Jordan. Research should be the first step in the process of EPR system design. None of the previous studies conducted used the AHP and FAHP in assessing and selecting the EPR systems.

Unlocking the Potential of E-Commerce in Yemen: Identifying Key Impacting Factors and Exploring Strategic Solutions

This study offers a comprehensive analysis of the e-commerce ecosystem in Yemen, identifying key opportunities and impacting factors to growth, and suggesting suitable strategies for e-commerce startups. The study employs an integrated methodical approach, combining a literature review, and data analysis using Grey Analytic Hierarchy Process (Grey AHP) and Grey Technique for Order of Preference by Similarity to Ideal Solution (Grey TOPSIS). The literature review identifies opportunities, challenges, and strategic solutions. The Grey AHP assesses the relative importance of opportunities and challenges. The Grey TOPSIS ranks the best strategies that e-commerce startups in Yemen can adopt to leverage these opportunities and manage the negative effects of the barriers. The results show that large market potential, the underserved market, and the growing middle class represent the most significant opportunities. In contrast, economic and political instability, logistical challenges, and the lack of trust in online payments are the most significant impacting factors. To overcome these challenges, the top three strategies recommended are building strategic partnerships, offering secure payment and delivery options, and targeting the underserved market. By implementing these strategies, the e-commerce ecosystem in Yemen can prosper, take advantage of opportunities, and contribute to the country’s economic development.

Site Selection for Sustainable Wind-Solar Hybrid Energy Harvesting Plant

The world’s energy landscape is undergoing rapid transformation as societies strive towards renewable and sustainable power sources in response to the need for energy security and climate change. Depletion of fossil fuels and increasing focus on environmental sustainability have been significant drivers in this global shift towards renewables. Among the promising solutions, solar-wind hybrid energy systems have gained attention, capitalizing on the complementary nature of solar and wind resources. However, selecting the optimal site for these hybrid plants is crucial for their successful implementation and efficiency. This research introduces a comprehensive methodology for site selection, seamlessly integrating the Delphi method and Analytic Hierarchy Process (AHP). The Delphi method harnesses expert consensus to distil essential criteria, while AHP offers a structured framework to evaluate and prioritize these criteria. The results showed successful utilization of the AHP and Delphi techniques for evaluating the optimal location selection among different cities for solar-wind hybrid energy harnessing in the northwest region of Pakistan. The key factors for selection of optimal location were identified through expert feedback and analysis. Among the selected key main criteria, resource availability and infrastructure and socio-economic factors emerged as the top-ranked criteria in this study. The results of this study hold significant relevance and should be duly considered for solar-wind power project site selection, while also offering opportunities for further enhancements in the future.

Assessment of multidimensional drought vulnerability using exposure, sensitivity, and adaptive capacity components.

This study provides a method for analyzing the drought-vulnerability index (DVI) from a multidimensional perspective that includes biophysical and social aspects, considering the Intergovernmental Panel on Climate Change's (IPCC) assessment. The proposed method generates the "exposure index (EI)", "sensitivity index (SI)", and "adaptive capacity index (ACI)" components of the proposed DVI using nine sub-indicators and 29 proxy variables. By using it throughout all of Turkey's provinces, the performance of the developed index was evaluated. In this study, the decision matrices were built utilizing expert knowledge, and the weights of the indicators and variables were obtained by using the Analytical Hierarchy Process (AHP) technique. Moreover, the values of these four indices were classified as "very high, high, moderate, low, and very low," and their geographical distribution across the country was drawn, as well as relevant patterns retrieved. The study's major results show that 17 of the 81 provinces are classified as "very high," 16 as "high," 15 as "moderate," 17 as "low," and the remaining 16 as "very low" drought vulnerable. Another significant result is that the majority of people in the country's south, center, and southeast rely on agriculture and are thus more vulnerable to drought due to socioeconomic underdevelopment in those regions.

Geospatial Multi-Criteria Evaluation Using AHP–GIS to Delineate Groundwater Potential Zones in Zakho Basin, Kurdistan Region, Iraq

Groundwater availability in the Zakho Basin faces significant challenges due to political issues, border stream control, climate change, urbanization, land use changes, and poor administration, leading to declining groundwater quantity and quality. To address these issues, this study utilized the Analytic Hierarchy Process (AHP) and geospatial techniques to identify potential groundwater sites in Zakho. The study assigned weights normalized through the AHP eigenvector and created a final index using the weighted overlay method and specific criteria such as slope, flow accumulation, drainage density, lineament density, geology, well data, rainfall, and soil type. Validation through the receiver operating characteristic (ROC) curve (AUC = 0.849) and coefficient of determination (R2 = 0.81) demonstrated the model’s accuracy. The results showed that 17% of the area had the highest potential as a reliable groundwater source, 46% represented high-to-moderate potential zones, and 37% had low potential. Flat areas between rivers and high mountains displayed the greatest potential for groundwater development. Identifying these potential sites can aid farmers, regional planners, and local governments in making precise decisions about installing hand pumps and tube wells for a regular water supply. Additionally, the findings contribute to the development of a sustainable groundwater management plan, focusing on improving water usage and protecting water-related ecosystems in the region. Identification of the optimum influencing factors, arrangement of the factors in a hierarchy, and creation of a GWPI map will allow further planning for groundwater preservation and sustainability. This project can be conducted in other areas facing droughts.

DETERMINATION OF FACTORS INFLUENCING DRUG USE USING THE FUZZY AHP METHOD AT THE NORTH SUMATRA PROVINCIAL NATIONAL NARCOTICS AGENCY (BNNP)

The phenomenon of drug abuse is primarily observed within the population characterized by experimental drug use, with a particular emphasis on individuals who are actively employed. Several factors, such as socioeconomic status and peer influence, have been identified as influential contributors in the occurrence of drug misuse. The objective of this study is to ascertain the determinants that impact individuals engaged in drug usage through the application of the Fuzzy Analytical Hierarchy Process (AHP) technique. The data for this research is derived from internal agencies, which aim to identify the elements that contribute to drug users' susceptibility to addiction and the subsequent development of drug dependency in individuals. The factors included in this study encompass Environment ( ), Family ( ), Economy ( ), Education ( ), and Personality ( ). The utilization of Fuzzy Analytic Hierarchy Process (AHP) for conducting data analysis methodologies. The AHP method yielded a value of λ=8.927, a CI of 2.65, and a CR of 87.39%. Moreover, during the Fuzzy Analytic Hierarchy Process (AHP) phase, it was determined that the primary determinant of drug abuse is (environment), exhibiting the highest average score of 0.8321, equivalent to 83.21%, in comparison to other components

Mapping of heterogeneity on groundwater level and potential zones along expeditiously urbanizing tropical coastal regions

The study of coastal groundwater potential is critical as freshwater availability is under tremendous stress due to increased coastal region development and noticeable monsoonal changing patterns over time. In addition to these factors, Odisha's coastal region has a larger drainage network in low-lying plains, which reduces freshwater recharge by increasing surface discharge. To sustain freshwater usage, the demarcation of the Groundwater potential zone (GWPZ) was done using Geographic Information System (GIS), Analytical Hierarchy Process (AHP), and Multi Influence Factor (MIF). Factors such as geomorphology, geology, land use/land cover, rainfall, lineament density, drainage density, elevation, slope, and soil were considered to accurately predict GWPZ. The AHP technique was used to construct a pairwise comparison matrix (PCM) and assign weights to each thematic layer, whereas the MIF method computes a recommended score for each layer based on the sum of the major and minor effect weights. The findings demonstrate that a significant portion of the study area falls into the "good" GWPZ (∼ 83% for both methods) category, indicating that the aquifer's storage is adequate. The output was validated by the Receiver operating curve (ROC) and groundwater prospects data. The ROC findings showed that the Area under curve (AUC) was 81% and 80.1% for AHP and MIF, respectively. This outcome signifies moderate to high precision indicating that the model could make accurate positive predictions. Analysis of pre-monsoon and post-monsoon water levels reveals spatial variations, with lower water levels indicating higher potential. Water levels in low-lying plains with high groundwater potential zones (GWPZ) are declining due to coastal erosion, sediment accumulation, limited infiltration, and increasing seawater intrusion. Continued groundwater abstraction may aggravate seawater intrusion despite favorable geological conditions. This study would be advantageous for coastal region decision-making involving water resource management and planning for sustainable development.

A fuzzy decision support model for online review-driven hotel selection by considering risk attitudes of customers

Online hotel reviews provide a vital information source for customers to select an optimal hotel, but a large amount of vague and unstructured information increases the difficulty of decision-making. From the perspective of customers’ risk attitudes, this paper proposes a novel fuzzy decision support model for hotel selection based on online reviews. Firstly, the useful information from online reviews is extracted by attribute extraction and sentiment analysis, and then this information is aggregated into the Probabilistic Linguistic Term Set (PLTS) by considering the weight of each review. Secondly, the improved linguistic scale functions are constructed from the perspective of customers’ risk attitude to convert PLTS into quantitative information. Thirdly, an integrated attribute weighting method is presented based on objective weights of the statistical measure and subjective weights of the Analytic Hierarchy Process (AHP) technique. Fourthly, an extended Combinative Distance-based Assessment (CODAS) method is developed to evaluate the performances of hotels. The effectiveness of the proposed model is verified by the practical case from TripAdvisor.com and the comparative analysis with the existing methods.

The factors obstructing the blockchain adoption in supply chain finance: a hybrid fuzzy DELPHI-AHP-DEMATEL approach

PurposeSupply chain finance (SCF) is an advanced financing solution for medium and small organizations. However, due to its nascent stage, SCF is still struggling with its application in the supply chain. The blockchain application in SCF can bring lots of opportunities and smart techniques to deal with financing to organizations. However, some factors restrict the proper adoption of blockchain in SCF. Therefore, this study aims to identify and analyze the factors obstructing blockchain adoption in SCF.Design/methodology/approachThe present study applied a hybrid fuzzy DELPHI-AHP-DEMATEL to validate and analyze the factors. The fuzzy Delphi techniques were adopted to validate the identified factors. Thereafter, the analytic hierarchy process (AHP) has been used to prioritize the validated factors. Further, the decision-making trial and evaluation laboratory (DEMATEL) method has opted to classify the factors into cause-and-effect groups.FindingsThe result of the study revealed that lack of technological competence and confidentiality leaking are the most prioritized factors and act as the prime factors for the obstacles in the blockchain application in the SCF. The application of the DEMATEL method revealed that the highest causing factor is authenticity, and the highest effecting factor is high cost.Practical implicationsThe current study enhances the knowledge and information of managers and policymakers about the challenges associated with the blockchain application in SCF as well as provides better insight to deal with various factors obstructing blockchain adoption in SCF.Originality/valueThe current study is the first of its kind, where factors obstructing blockchain adoption in SCF are identified and validated with the help of experts and practitioners by incorporating the fuzzy Delphi method. Thereafter, the validated factors are prioritized by using fuzzy AHP and fuzzy DEMATEL techniques helps to identify the cause-and-effect group, which opens the door for future research work.

Hierarchical Q-learning-enabled neutrosophic AHP scheme in candidate relay set size adaption in vehicular networks

Cooperative candidate relay sets (CRS) in opportunistic broadcast paradigms can significantly improve the performance efficiency of traditional broadcast schemes by simultaneously scheduling multiple vehicles in the data packet transmission process. Nonetheless, multiple relay synchronization may cause enormous data redundancy and high delays in data delivery, resulting in a high cooperative transmission cost. High vehicle velocities and vehicular topology restrictions, including intersections, exacerbate the cooperative transmission cost. Motivated by a trade-off between delay and delivery ratio via reducing duplicate data packets and redundant relays, we address this gap in this paper. To this end, we propose an adaptive candidate relay set (ACRS) size scheme based on the Neutrosophic Set Analytic Hierarchy Process (NS-AHP) technique assisted by a Q-learning algorithm. The NS-AHP pair-wise comparison matrix includes; redundancy, cooperative-based efficiency, and relay set stability as the decision-making attributes. Meanwhile, we use a hierarchical Q-learning approach based on the time-varying vehicular environment to adjust the relative preference of the attributes and alternatives (i.e., various CRS sizes) over each other. To optimally learn the relative preference values of the attributes and alternatives over each other, reward functions are set dynamically at both levels. Comprehensive simulations via NS-2 and SUMO are carried out to assess the efficacy of our ACRS scheme compared to three commonly used baseline techniques of fixed size, threshold-based, and probability-based techniques. Overall, the average yields obtained from the experimental outcomes in the urban and highway scenarios show that the ACRS scheme, on average, improves the packet delivery ratio by 3.77%, 5.36%, and 1.35%; reduces the single-hop delay by 34.78%, 42.085%, and 19.39%; reduces the end-to-end delay by 34.76%, 42.72%, and 21.35%; improves the transmission throughput by 34.24%, 41.54%, and 19.305%; and reduces the redundancy ratio by 43.69%, 50.66%, and 24.32% compared to the fixed size, threshold-based, and probability-based techniques, respectively.

Mapping analytical hierarchy process research to sustainable development goals: Bibliometric and social network analysis

The drive to achieve the Sustainable Development Goals (SDGs) becomes more urgent as the 2030 deadline draws near, increasing research in various sectors. Nevertheless, studies that systematically map Analytical Hierarchy Process (AHP) publications with the SDGs need to be more conspicuously lacking. Our study adds a new perspective to the field by creatively bridging this knowledge gap using the Elsevier SDG Mapping Initiative. To find research clusters, trends, and themes linked to SDGs and their connection to environmental sustainability, we thoroughly analyzed 29,897 publications from 2012 to 2022. The analysis showed that SDG 15, SDG 7, SDG 12, SDG 13, and SDG 11 were the top five SDGs, with an environmental focus among the 17 SDGs. These top SDGs had many clusters connected to them, illustrating various sustainability-related problems. The study also looked at connections between SDGs, the nations with the highest rates of productivity, the top contributors, and the journals with the highest citation counts. We discovered three separate SDG clusters using co-occurrence network analysis, each representing a different SDG. We discovered relevant SDGs using Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis and centrality indicators like eigenvector and betweenness. This novel method for publishing analysis combines an AHP focus that aligns with the SDGs with social network analysis and centrality metrics. Our research advances knowledge of how the AHP technique can assess initiatives supporting the SDGs. We offer essential insights into prioritizing sustainable development measures by identifying research clusters, trends, and issues related to environmental sustainability. This study highlights the subject's most important SDGs, productive nations, helpful organizations, and significant journals.

Landfill Site Selection Using Multi-Criteria Decision Analysis, Remote Sensing Data, and Geographic Information System Tools in Najran City, Saudi Arabia

Many practical issues arise when dealing with solid waste management, and there are also environmental effects to be considered. Selecting landfill sites requires extra care with respect to many factors such as the environment, health hazards for people, and the cost of transportation. Furthermore, cities have their own rules, methods, and practices for managing and selecting the best locations for collecting solid waste. In this research, multi-criteria decision analysis (MCDA) was presented and used to evaluate the appropriateness of and suggest the best locations for landfill sites in Najran, KSA. Some remote sensing data and the ArcGIS software were used to prepare nine thematic layers, including drainage density, groundwater depth, land use, soil type, road network, surface elevation, surface slope, distance from residential areas, and distance from protected areas. To evaluate the layer weightings, a questionnaire with pairwise comparisons was distributed among experts and analyzed using the analytical hierarchy process (AHP) and fuzzy set technique. The one-factor-at-a-time (OFAT) sensitivity test was conducted to test the sensitivity of the evaluated weightings. A landfill suitability index (LSI) map was created using raster calculator tools and divided into five classes: limited suitability (LSI value 1.39–2.49), least suitable (2.50–3.03), relatively suitable (3.04–3.48), suitable (3.49–3.91), and most suitable (3.92–4.66). According to the statistical analysis, 18.0% and 18.2% of the total area were within the most suitable and suitable landfill regions, while 21.2%, 14.9%, and 9.5% accounted for relatively suitable, least suitable, and limited suitability areas, respectively. The employed technique and its findings can provide an appropriate guideline to assist the municipality of Najran city, regional planners, and decision-makers in selecting an optimal landfill site in the future. This study also presented some recommendations to enhance the suitability map of landfill sites in Najran city.

Assessing groundwater potential zones and artificial recharge sites in the monsoon-fed Murredu river basin, India: An integrated approach using GIS, AHP, and Fuzzy-AHP

The sustainable management of water relies heavily on groundwater resources, and an important aspect of their effective utilization is artificial recharge. In the specific case of the Murredu watershed in India, a comprehensive approach is proposed in this research, integrating Geographic Information Systems (GIS), Remote Sensing (RS), and Multi-Criteria Decision Making (MCDM) techniques. The aim is to delineate groundwater potential zones (GWPZs) and identify suitable locations for artificial recharge. Several thematic layers, such as slope, drainage density, geomorphology, land use land cover (LULC), curvature, soil, topographic wetness index (TWI), rainfall, distance from the river, and elevation, were considered in this study. To ascertain the relative importance of these thematic maps in influencing groundwater availability and recharge, the Analytic Hierarchy Process (AHP) and Fuzzy-AHP techniques were employed to assign weights. Utilizing a weighted overlay technique within a GIS environment, the GWPZs map was generated. Within the study area, the GWPZs were categorised as poor, moderate, and high based on the AHP and Fuzzy-AHP models. According to the AHP model, 14.93% of the GWPZs in the region were classified as poor, 73.53% as moderate, and 11.54% as high. On the other hand, the Fuzzy-AHP model classified 14.02% as poor, 76.55% as moderate, and 9.44% as high. The accuracy of these classifications was verified using the receiver operating characteristic curve (ROC) and area under the curve (AUC), resulting in accuracy rates of 71.4% for AHP and 77.6% for Fuzzy-AHP. Additionally, the study employed RS and GIS techniques to develop a map by overlaying the drainage density and lineament density maps. This approach helped identify 126 potential sites for artificial recharge based on the best-performing Fuzzy-AHP model. The insights gained from this study facilitate the sustainable management and planning of groundwater resources, ensuring their availability and sustainability for future generations.

Impact of Authentic Leadership traits in Engineering Sector using MCDM

This study aims to develop a conceptual model that establishes a connection between Authentic Leadership (AL), employee engagement, and organizational innovation within Pakistan's engineering sector. Employing a Multi-Criteria Decision-Making (MCDM) technique, the study investigates the interaction and impact of workers on organizational innovation, generating benefits for both industry practitioners and the academic community. The findings highlight the substantial influence of four key AL traits, namely balanced processing, internalized moral perspective, relational transparency, and self-awareness, on work engagement[8]. By applying the Analytic Hierarchy Process (AHP) and utilizing decision making software, the study identifies the internalized moral perspective as the most crucial criterion for AL outcomes, with a weight of 0.0483. Balanced processing (weight: 0.1220), relational transparency (weight: 0.20894), and self-awareness (weight: 0.25891) follow as subsequent priorities. These outcomes contribute to the development of theoretical understanding in the field. Furthermore, they provide valuable insights to the engineering sector, enabling the cultivation of employee engagement and the enhancement of organizational innovation.The research focuses on elucidating the relationships between AL, employee engagement, and organizational innovation in the context of Pakistan's engineering sector. By adopting a comprehensive MCDM approach, the study offers a thorough analysis of the factors influencing employee engagement, with particular emphasis on the identified AL traits. The findings underscore the significance of balanced processing, internalized moral perspective, relational transparency, and self-awareness as drivers of work engagement[9]. Moreover, the application of the AHP technique reveals the priority weights assigned to these traits, highlighting the critical role of the internalized moral perspective criterion in achieving AL outcomes.The results of this research carry implications for both practitioners and scholars. For the engineering sector in Pakistan, embracing and implementing AL practices can yield substantial benefits, fostering a work environment that stimulates employee engagement and drives organizational innovation. By prioritizing the identified AL traits, organizations can effectively channel their resources and efforts towards enhancing employee engagement and promoting innovation. From an academic standpoint, this study contributes to the existing literature by providing empirical evidence and a conceptual model that sheds light on the interplay between AL, employee engagement, and organizational innovation. The findings serve as a foundation for further theoretical development and future research endeavors in this domain.

An integrated fuzzy AHP and fuzzy TOPSIS approach for screening backfill materials for contaminant containment in slurry trench cutoff walls

The inclusion of backfill material is crucial for the effective containment of contaminants in a slurry trench cutoff wall. However, selecting the optimal backfill material is complex and involves multiple criteria. This study aimed to develop a new approach to assist in the selection process by rationally dealing with the subjective judgment of decision makers. The approach employed fuzzy analytic hierarchy process (AHP) and fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methods. Initially, consistent judgment matrices were established based on a unique consulting questionnaire. The fuzzy AHP method used Buckley's method to calculate the fuzzy weights of pairwise comparisons. The fuzzy TOPSIS method was then employed to rank and evaluate four different backfill materials. The proposed methodology was successfully implemented at a real contaminated site in China to select the appropriate backfill material for construction of a slurry trench cutoff wall. Based on the proposed integrated methodology, fiber reinforced reactive magnesia-activated slag-soil-bentonite (FMSB) was determined as the most appropriate backfill materials for contaminant containment in slurry trench cutoff walls at the site reported in this study.

Urban flood risk assessment using AHP and geospatial techniques in swat Pakistan

The rapid urbanization and changing climate patterns in Swat, Pakistan have increased the vulnerability of urban areas to flood events. Accurate assessment of flood risk is crucial for effective urban planning and disaster management. In current research study flood hazard index was developed using analytic hierarchy process (AHP) technique in combination with the geographical information system (GIS) environment in Swat, Pakistan. The study integrates various data sources, including topographic maps, land use/land cover information, rainfall data, and infrastructure data, to develop a comprehensive flood risk assessment model. The weights obtained from the AHP analysis are combined with geospatial data using a geographic information system (GIS) to generate flood risk maps. The flood hazard levels were categorized into five distinct classes: very low, low, moderate, high, and very high. Using the GIS-AHP approach, higher weights were assigned to rainfall, distance to river, elevation, and slope in comparison to NDVI, TWI, LULC, curvature, and soil type. The flood hazard map was then reclassified for each parameter. By overlaying these maps, it was determined that 5.6% of the total area is classified as very high flood risk, 52% as high risk, 39.3% as moderate risk, and 3.1% as low risk. The developed comprehensive flood risk assessment model in current study can identify high-risk areas, prioritize mitigation measures, and aid in effective urban planning and disaster management.

A comprehensive approach to selecting mine transportation system using AHP and FUZZY-TOPSIS

Mine transportation approximately accounts for more than half of operating costs. Therefore selection of the appropriate mine transportation system by considering the effective criteria has become an important issue in mining engineering. A hybrid decision support system based on Analytical Hierarchy Process (AHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) was proposed to assess criteria and alternatives for balancing haulage distance, continuity, flexibility and reliability, which could provide the suitable balance between different goals, such as costs and safety. An application of this approach is carried out through the Sungun copper mine as case study. For this purpose, the production capacity, medium and short-term production plan, conditions of mining benches and ramps and future development plans collected from chosen mine located at the East Azerbaijan Province, Iran. This research has been studied comprehensively in terms of technical, economic, environmental, society, site information, geological and geo-mechanically criteria. More than 170 criteria were identified and classified under six main categories. To select the mine transportation system, the importance of each criteria is first measured relative to each other, then the importance of each option is evaluated for each criteria and were filtered to 55 items. The proposed model is based on the combination of the AHP and fuzzy TOPSIS. The hybrid model has advantages such as the possibility of using paired comparison and considering uncertainty. Finally, the in-pit crushing and conveying is selected as the best alternative, the truck-front shovel and truck-backhoe system are in the next priorities, respectively 45.2, 28.4 and 26.4%. In summary, from the results of the research, it can be mentioned to present the effective criteria in the selection of the transport system of open pit mines, to calculate their weight, to provide a framework for the selection of the transport system of open pit mines by considering the uncertainties.