Technique For Order Of Preference By Similarity To Ideal Solution Model Research Articles

A Multimoora-based MCDM model under picture fuzzy environment for converting municipal solid waste to energy in Himalayan Region: A sustainable technology assessment

Municipal solid waste (MSW) has long been regarded as a reliable and efficient source of waste-to-energy conversion. However, the conversion approach has many drawbacks that limit its application. This paper explores MSW to energy innovations as a potential solution to understand better MSW's potential applications in energy generation, existing technologies, technological feasibility, and environmental effect. The study used a Multimoora-based MCDM model to convert MSW to energy in a picture-fuzzy environment to build more effective technology for future generations. The incineration, pyrolysis, gasification, and bio-methanation conversion technologies, were explored and assessed based on various physical and chemical criteria like energy efficiency, capacity, useful side product, environmental effect, waste material, cost aspect, temperature and the system's long-term utilization from MSW to energy. A comparative analysis was done to verify the superiority of the proposed MCDM model with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model. According to the suggested Picture fuzzy MCDM model, the weight attributions for all seven criteria that determine the technique's output are waste material (0.1602) > temperature (0.1503) > useful side product (0.1456) > environmental effect (0.1370) = capacity (0.1370) > cost aspect (0.1360) > energy efficiency (0.1340). Each technique underwent evaluation and comparison, then ranked according to the proposed MCDM model from most to least preferred. The results of both picture fuzzy Multimoora-based MCDM and TOPSIS models showed that, although other technologies are also effective, as having a high output, the Bio-methanation technology is highly effective in converting MSW to energy with the least environmental damage.

HVAC Systems Evaluation and Selection for Sustainable Office Buildings: An Integrated MCDM Approach

Heating, Ventilation, and Air-Conditioning (HVAC) systems are critical components of maintaining an indoor air quality that ensures the thermal comfort of occupants in diverse building types. However, HVAC systems are also responsible for a substantial portion of the total energy consumption of commercial and industrial office buildings. This paper presents an integrated approach of two powerful MCDM techniques: the Best-Worst-Method (BWM) and The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in order to evaluate and rank HVAC systems to ensure the best selection toward designing a sustainable office building. A set of conflicting criteria reported by international sustainable assessment centers were employed along with various HVAC systems to develop what is called herein a BWM-based TOPSIS model in order to conduct such a novel research attempt. Within the context of the investigated office building herein, the mini-package ductless system appears to be the best choice. This study could be further enhanced by including additional criteria and a larger sample size in future studies.

Environmental, economic, and social sustainability assessment: A case of using contaminated tailings stabilized by waste-based geopolymer as road base

Contaminated tailings, e.g., iron tailings, could be stabilized by low-carbon geopolymers for recycling as road base, but the sustainability has yet to be evaluated comprehensively. This study developed a sustainable framework from the life cycle perspective, consisting of quantitative indicators in environment, society, and economy, to assess five stabilization cases (i.e., M1, M2, C1, C2, and cement). Moreover, a modified AHP (Analytic Hierarchy Process)-CRITIC (CRiteria Importance Through Inter-criteria Correlation)-TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model was applied to select the most sustainable stabilization method. The sustainability scores of four cases using geopolymers were higher than that of the cement case (0.22), with C2 (0.75), C1 (0.64), M1 (0.56), and M2 (0.54), respectively. Sensitivity analysis confirmed that the assessment results were relatively stable, especially when the subjective weight of the economy was not the highest (the cement counterpart had economic advantages). This study constituted a novel approach to complement the selection of sustainable stabilization cases, bridging the gap of focusing exclusively on green stabilization performance.

Watershed prioritization using morphometric analysis by MCDM approaches

Due to the highly complex nature of human and ecological systems, soil erosion has increased considerably. Therefore, understanding watersheds and future forecasting circumstances using a watershed approach must be developed significantly on a spatial dimension. It's crucial to understand the watershed's key zones with a lineage of soil erosion as they undergo stream displacement and soil erosion issues. So, there is a need for proper soil and water management treatments to overcome continuous soil loss by runoff and other ecological problems in the Pindar watershed. In this study, an attempt has been made to explore several morphometric characteristics of the Pindar River watershed, which is located in the Uttarakhand districts of Chamoli and Bageshwar, using Geographic Information System (GIS) and remote sensing techniques for prioritizing the sub-watersheds in order to develop a suitable management plan to combat land degradation in order to assist in future management and conservation by four Multi-Criteria Decision Making (MCDM) techniques, viz., Analytical Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (FAHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Finally, the performance of MCDM prioritization techniques was evaluated. For this purpose, 13 morphometric characteristics, including basic, linear, form, and landscape, were extracted and analyzed using an SRTM DEM with a spatial resolution of 30 m. Sub-watersheds' prioritization revealed that, according to the AHP, FAHP, TOPSIS, and VIKOR models, sub-watershed 26 is the most prone to erosion. The findings demonstrated that morphometric criteria are highly effective at identifying erosion-prone locations. The evaluation of the MCDM approaches has been done based on the percentage of changes and the intensity of the changes. The results indicated that the FAHP, with a change percentage of 71.21, has more efficiency and accuracy than the VIKOR, AHP, and TOPSIS methods, with 62.89%, 62.88%, and 62.12%, respectively. The results of the evaluation of the intensity of changes showed that the FAHP model had the highest rate of change (1.22), whereas the AHP, TOPSIS, and VIKOR methods, with the intensity of changes of 1.09, 1.09, and 1.07, placed in the next rank. Concerning the values of the percentage of changes and the intensity, it can be stated that the FAHP model has been more accurate than the other models.

An Empirical Study on the Environmental Carrying Capacity of Marine Resources Based on the Entropy-Weight TOPSIS Model

Yang, S.; Ren, L., and Gou, L., 2022. An empirical study on the environmental carrying capacity of marine resources based on the entropy-weight TOPSIS model. Journal of Coastal Research, 38(5), 1037–1049. Coconut Creek (Florida), ISSN 0749-0208. The sustainable development of the marine economy has drawn increasing attention from the countries of the world. To realize the compatibility between marine resources and environmental carrying capacity and marine economic development, it is important to fully understand the environmental carrying capacity of marine resources and its evolutionary trends. After an in-depth discussion on the definition of marine resources and environmental carrying capacity, an assessment system was constructed, incorporating 28 indicators that cover the development of the marine economy, marine resources carrying capacity, and the marine environmental carrying capacity. Following this, the entropy-weight Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model and the kernel density estimation method were used to assess the environmental carrying capacity and internal carrying capacity of Qingdao's marine resources from 2007 to 2018. The empirical results show that the environmental carrying capacity of marine resources in Qingdao presented a declining trend between 2007 and 2010, followed by a noticeable upward trend from 2011 to 2014, and then another downward trend in 2015. These findings suggest that both the carrying capacity of marine resources and environmental carrying capacity are still under threat, as indicated by a low capacity assessment score overall. Specifically, whereas the development of the marine economy progressed steadily, marine resources carrying capacity fluctuated, reaching a maximum value of 0.3251 in 2007, and the overall marine environmental carrying capacity presented a fluctuating upward trend, which was generally consistent with the changes in marine resources and environmental carrying capacity. The results show that the model can consider many factors simultaneously, evaluate the marine resources and environmental carrying capacity, and provide valuable insights into the study of marine carrying capacity and policy implications for achieving sustainable development in the marine sector.

Sites selection for a potential radioactive waste repository in Peninsular Malaysia: GIS-based weight linear combination and multi-criteria decision-making analysis

This paper aims to determine the suitable places for a radioactive waste repository in Peninsular Malaysia to implement a permanent disposal facility for disposal sealed radioactive sources (DSRS). The sole Malaysia interim waste storage that stores a large proportion of DSRS was expected to be occupied by 2025 fully. Currently, the nation’s licensing board promoted the borehole disposal facility to resolve the full capacity dilemma. The potential sites were determined by the geographical information system (GIS) based Weight Linear Combination (WLC) analysis, integrating the improved Analysis Hierarchical Process (improved AHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The sensitivity analysis was applied to identify the main contributing factors for corresponding Peninsular Malaysia selection. Ten parametric criteria and three exclusion criteria are applied to assess the potential areas and screen out the unfavorable regions, respectively. Results indicated the final composite map presents 435 areas of very high suitability class with 17.5% coverage from the total suitability class. The top 5 largest candidates with high potentiality are Jerantut & Ulu Lepar, Bandar Tun Razak, Pertang & Simpang, Pertang, Tanjung Ipoh, and Labis, where come from three provinces: Pahang, Negeri Sembilan and Johor. By TOPSIS model, the ranks for these five candidates are Jerantut & Ulu Lepar, Bandar Tun Razak, Tanjung Ipoh, Labis and Simpang Pertang. The model revealed that the suitability ranks is proportional to its area sizes in the approximate values of criteria. The three main contributing factors in Peninsular Malaysia are hydrogeology, seismicity and lithology, which are strongly recommended to involve in other corresponding site selection project.

IFWG-TOPSIS Model for Supporting Infant Failure Assessment in an Offshore Wind Turbine System

Introduction: System failure analysis is an essential aspect of equipment management. This analysis improves equipment reliability and availability. However, to assess infant failure under dynamic criteria, reliability engineers require special models. Method: Hence, this study uses an Intuitionistic Fuzzy Weighted Geometric (IFWG) and Intuitionistic Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods to develop an IFWG-TOPSIS model for infant failure assessment. We consider a case study of Offshore Wind (OFW) turbine infant failure assessment. Result: During the model evaluation, this study considered an infant failure of the turbine's main shaft, blade bearings, pitch system, jacket and monopile support structure, and gearbox. Risk factor, spare part weight, technical importance, cost, and complexity criteria were used to evaluate these components’ reliability. The results show that the blade bearings (S2) and main shaft are the most and least reliable components, respectively. To validate the model’s performance, we compared its results with Gümüş and Bali’s and standard VIKOR models results. These models selected the same components as the most and least reliable components, respectively. Thus, the proposed model is suitable for OFW turbine’s infant failure assessment. Discussion: It can be deduced that the use of the modified IFWG operator to calculate the intuitionistic fuzzy distance measure in standard TOPSIS model as the capacity to produce realistic results that can compete with existing decision-making methods. Conclusion: This study has investigated the use of techno-economic criteria for OFW turbine components’ infant failure assessment. A fuzzy-based model was used to establish the connection between the criteria and the components. We developed this model using the Intuitionistic Fuzzy Weighted Geometric (IFWG) and Intuitionistic Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. Using experts’ judgments, data were obtained for the developed model evaluation and validation.

A TOPSIS-Inspired Ranking Method Using Constrained Crowd Opinions for Urban Planning.

Crowdsourcing has become an important tool for gathering knowledge for urban planning problems. The questions posted to the crowd for urban planning problems are quite different from the traditional crowdsourcing models. Unlike the traditional crowdsourcing models, due to the constraints among the multiple components (e.g., multiple locations of facilities) in a single question and non-availability of the defined option sets, aggregating of multiple diverse opinions that satisfy the constraints as well as finding the ranking of the crowd workers becomes challenging. Moreover, owing to the presence of the conflicting nature of features, the traditional ranking methods such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) cannot always be feasible as the optimal solutions in terms of multiple objectives cannot occur simultaneously for the conflicting cases (e.g., benefit and cost criteria) for urban planning problems. Therefore, in this work, a multi-objective approach is proposed to produce better compromised solutions in terms of conflicting features from the general crowd. In addition, the solutions are employed to obtain a proper ideal solution for ranking the crowd. The experimental results are validated using two constrained crowd opinion datasets for real-world urban planning problems and compared with the state-of-the-art TOPSIS models.

URBAN RAIL TRANSIT PASSENGER SERVICE QUALITY EVALUATION BASED ON THE KANO–ENTROPY–TOPSIS MODEL: THE CHINA CASE

In order to evaluate the URTPSQ (Urban Rail Transit Passenger Service Quality) comprehensively, find the shortage of URTPSQ, find out the difference between the actual service situation and the passenger’s expectation and demand,and provide passengers with better travel services, a passenger-oriented KANO–Entropy–TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed and applied in this paper. Firstly, a KANO model is applied to select the service quality indicators from the 24 URTPSQ evaluation sub-indicators, according to the selection results, the KANO service quality indicators of URTPSQ are constructed. Then the sensitivity of the KANO service quality indicators based on the KANO model are calculated and ranked, the PS (Passenger Satisfaction) of each KANO service quality indicator by using the Entropy–TOPSIS method is calculated and ranked. Based on the difference between the sensitivity degree rank and the satisfaction degree rank of each KANO service quality indicator, determine the service quality KANO indicators of the URTPSQ that need to be improved significantly. A case study is conducted by taking the Chengdu subway system in China as a background. The results show that the Chengdu subway operation enterprises should pay attention to the must-be demand first, then the one-dimensional demand, finally the attractive demand. The three indicators, including transfer on the same floor in the station, service quality of staffs of urban rail transit enterprises,and cleanness in the station and passenger coach, need to be improved urgently. For the managers and operators of urban rail transit system, the passengers’ must-be demand should be satisfied first if the KANO model is applied to evaluate the service. The indicators with highest sensitivity degree and lowest TOPSIS value should be improved based on the KANO–Entropy–TOPSIS model.

Developing a Fuzzy TOPSIS Model Combining MACBETH and Fuzzy Shannon Entropy to Select a Gamification App

Due to the important advantages it offers, gamification is one of the fastest-growing industries in the world, and interest from the market and from users continues to grow. This has led to the development of more and more applications aimed at different fields, and in particular the education sector. Choosing the most suitable application is increasingly difficult, and so to solve this problem, our study designed a model which is an innovative combination of fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the Measuring Attractiveness by a Categorical Based Evaluation Technique (MACBETH) and Shannon entropy theory, to choose the most suitable gamification application for the Industrial Manufacturing and Organisation Systems course in the degree programmes for Electrical Engineering and Industrial and Automatic Electronics at the Higher Technical School of Industrial Engineering of Ciudad Real, part of the University of Castilla-La Mancha. There is no precedent in the literature that combines MACBETH and fuzzy Shannon entropy to simultaneously consider the subjective and objective weights of criteria to achieve a more accurate model. The objective weights computed from fuzzy Shannon entropy were compared with those calculated from De Luca and Termini entropy and exponential entropy. The validity of the proposed method is tested through the Preference Ranking Organisation METHod for Enrichment of Evaluations (PROMETHEE) II, ELimination and Choice Expressing REality (ELECTRE) III, and fuzzy VIKOR method (VIsekriterijumska optimizacija i KOmpromisno Resenje). The results show that Quizizz is the best option for this course, and it was used in two academic years. There are no precedents in the literature using fuzzy multicriteria decision analysis techniques to select the most suitable gamification application for a degree-level university course.

A Fuzzy TOPSIS Approach to Ranking the Effectiveness of Corrective Feedback Strategies: Monolingual Persian Versus Bilingual Turkmen EFL Learners

Corrective feedback (CF) as a multifaceted practice needs to be explored from different perspectives. Achieving relative consensus among language teachers and experts in a particular context on the most effective CF strategy for monolingual and bilingual language learners appears to be understudied. As such, a fuzzy TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model was applied to accommodate varied and conflicting opinions in ranking the effect of three corrective feedback strategies including mid-focused oral metalinguistic CF, written metalinguistic CF, and oral/written metalinguistic CF. To this end, 79 monolingual Persians and 79 bilingual Turkmens aged between 13 and 18 from two language institutes in Golestan Province of Iran participated in the study comprising three experimental and one control group each. The experimental groups were provided with CF strategies on their most recurrent grammatical errors detected through pretests while the control groups received none. The results of the fuzzy TOPSIS approach ranked oral/written metalinguistic CF and oral metalinguistic CF as the best strategies for monolingual Persians and bilingual Turkmens respectively. The fuzzy TOPSIS approach provided experts with the opportunity to include their opinions on the weight of criteria and the impact of CF strategies towards enhancing the experts’ agreement on the issue. It was shown that a single CF strategy might not be appropriate for all EFL learners in different contexts. The approach also provided a framework for soliciting wider participation of the experts when conditions favor the application of multi-criteria decision-making methods, or speedier assessments are required.

A Hotel Recommender System for Tourists Using the Artificial Bee Colony Algorithm and Fuzzy TOPSIS Model: A Case Study of TripAdvisor

Recommendation systems play an indispensable role in tourists’ decision-making process. An important issue for tourists concerns the selection of accommodation in accordance with the criteria on their minds, which may include several items at the same time. This paper proposes a novel approach to recommendation systems in the tourism industry involving a combination of the Artificial Bee Colony (ABC) algorithm and the fuzzy TOPSIS model. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a multi-criteria decision-making method, has been utilized to optimize the system. The solution presented in this research includes two major parts, where the employed ABC algorithm has been improved and is more efficient than the standard version. This research has addressed the TripAdvisor dataset and presented a method for hotel recommendations based on user preferences according to real data. The obtained results demonstrate the high accuracy of the method presented in the research.

A TOPSIS model for understanding the authors choice of journal selection

Subsequent to preparation of an article, authors start to look for a suitable journal to submit. Authors are assumed to select the journals by considering their future expectations regarding the maximization of prospective impact of the study, increasing the probability of acceptance and minimizing the total time consumed until the paper is published. Furthermore, the scope of a candidate journal should be in line with paper’s content. Currently, it is possible to find these journal related facts (such as average waiting times, acceptance rates, impact factor and etc.) on the web pages of the journals. However, the exact effect of these factors, and how to incorporate them into modeling, are yet unclear; further research is required to explore them. On the other hand, we know that Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) can be a useful approach to rank the journal alternatives. We require corresponding weights of factors to obtain a complete decision making model. If the correct weights of these factors for such a TOPSIS model can be estimated, we can understand the magnitude of their corresponding effects. Thereby, we can explain the journal selection decision by using an analytical approach. Therefore, the main purpose of this paper is to find appropriate weights of these factors that can explain why already published papers were submitted to their current journals. To the authors’ knowledge, this paper is the first to search for weight of factors in TOPSIS, where the actual decisions are known a priori. For testing purposes, we create our data set by collecting the already published papers (in year 2019) which has the “environmental risk” term at the title/abstract or keywords. We test different TOPSIS models (with different random weights) for each of the papers and the rank the journal alternatives. If the first, second and the third journal alternative is the actual journal that published the paper, we assume that the model predicts accurately. As a conclusion, the TOPSIS model which predicts the journal for the published papers much more accurately is accepted as the valid decision making model. Inevitably, we have certain assumptions regarding to this model. We assume that the authors are informed about the journal facts and make rational decisions about journal selection.

Maritime accident prevention strategy formulation from a human factor perspective using Bayesian Networks and TOPSIS

Human factors contribute to majority of maritime accidents. This study proposes an advanced methodology for maritime accident prevention strategy formulation from a human factor perspective. It is conducted by incorporating Bayesian network (BN) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in a multi-criteria decision-making system. In order to develop rational accident prevention strategies, this work integrates Multiple Correspondence Analysis (MCA), Hierarchical Clustering (HC) and Classification Tree (CT) to generate strategies and describes accident types as criteria for a new multi-criteria risk-based decision-making system. Specifically, MCA is performed to detect patterns of contributory factors explaining maritime accident types. It is complemented by HC and a CT, aiming at creating different classes of vessels. Next, a Bayesian-based TOPSIS model is built to illustrate the features of multiple criteria and the relations among alternatives (i.e. strategies), so as to select the best-fit strategies for accident prevention. The results show that the information, clear order, and safety culture are the three most effective recommendations for maritime accident prevention considering human errors, which presents new insights for accident prevention practice for maritime authorities.

European hub location problem for China Railway Express in the context of the Belt and Road Initiative

ABSTRACT Freight trains between Europe and China (China Railway Express) are a central component of the Belt and Road Initiative. In recent years, the service has experienced significant growth, however operational problems still remain. Seeking a solution, this paper used a hierarchical spatial aggregation process based on EU transportation policy to identify 87 origin nodes. Distance-based weighted centrality measures and a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model ranked node centrality in European rail, road, and waterway networks. The 10 highest-ranking nodes served as candidate hubs for the mixed-integer linear programme, which considered time-definite, multimodal transportation and penalised partially vacant trains. Berlin, Budapest, Duisburg and Lille were chosen as optimal hub locations.

Identification of effective factors to select energy recovery technologies from municipal solid waste using multi-criteria decision making (MCDM): A review of thermochemical technologies

Thermochemical technologies used to burn municipal solid waste are one of the relatively new and appropriate methods for waste management. By burning waste, heat and gases have arisen which can be used as the energy source to generate electricity. Due to the high cost, pollution emissions and diversity of such power plants, comprehensive studies are required. Therefore, the purpose of this study is to investigate the thermal methods in the field of waste management and to optimum for the most suitable methods. The selected thermochemical technologies include incineration, gasification, plasma, and pyrolysis. Data gathering was done through a questionnaire completed by experts. The decision-making models based on the Analytical Hierarchical Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are proposed to select the best thermochemical technology by the technical, economic, and environmental criteria. Ultimately, the environmental criteria (0.355), economic criteria (0.338) and, technical criteria (0.307) were introduced as the most effective criterion in choosing thermal methods respectively. The results of both AHP and TOPSIS models showed that the plasma method is the optimal thermochemical technology in terms of three existing criteria. Incinerator, gasification, and pyrolysis systems were ranked next.

Waste Reduction for Green Service Supply Chain—the Case Study of a Payment Service Provider in Iran

Analyzing and designing how service is provided to the customer is crucial for sustainable supply chains in services. In this respect, there can be barriers to applying sustainable improvements due to regulations, practices and customer culture. This study is focused on finding the waste produced by the service of one of the biggest payment service provider (PSP) companies in Iran and how to meet the essential needs of the sustainable supply chain. It has been observed that using thermal papers as a biohazardous material causes environmental problems and even it is hazardous to mix them with normal paper waste in the recycling process. Moreover, preventive maintenance of the thermal printers itself causes a huge number of unnecessary shuttles between the customers and service suppliers, which represents a source of CO2 emission, traffic—especially in the capital—and high maintenance costs for the company. Three main alternatives to the thermal paper receipt were analyzed and ranked by means of a TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) model, which employed the sustainability pillars and the technical point of view as evaluation criteria. The priorities against the set of criteria were obtained by means of surveys, which targeted a sample of customers and a pool of experts. The results highlighted that customers’ habits and legislation are the most important barriers to the transition to a more sustainable service.

Catchment-scale soil conservation: Using climate, vegetation, and topo-hydrological parameters to support decision making and implementation

The geomorphometric analysis of watersheds provides useful quantitative information on stream hydrology and potential landscape change that can be used by soil conservation decision makers to determine areas prone to land degradation. In this study, we develop a methodology for the assessment of catchment-scale sensitivity to sediment yield using various topo-hydrological, vegetation, and climatic parameters using four multi-criteria decision making (MCDM) techniques: the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR), weighted-sum analysis (WSA), and combined factor (CF). To identify the most important factors affecting sediment yield and soil erosion, a model incorporating principle component analysis with MCDM was devised, using infiltration number (IF), drainage density (Dd), length of overland flow (Lo), channel maintenance (C), stream frequency (Fs), and ruggedness number (Rn) as indices of sediment and erosion risk. Data from a previous study that employed the RUSLE3D model and sediment-yield field data were used to validate the results. The TOPSIS model achieved the highest correlation with the RUSLE3D results. The correlation of watershed activities to the experimental erosion and sediment prioritization results is 0.32. The TOPSIS results indicate that all 23 sub-watersheds yielded moderate amounts of sediment. Based on the VIKOR method, 17.39% (78.96 km2) of the region was classified as having very high erodibility, 26.08% (241.93 km2) high erodibility, 34.78% (225.95 km2) moderate erodibility, and 21.73% (105.05 km2) low erodibility. Considering the high sensitivity of Taleghan watershed to soil erosion, it is recommended that conservation efforts be implemented to minimize land degradation in the area. This methodology can be adapted to other regions that lack detailed topo-hydrological, vegetation, or climatic data.

Landfill site selection via integrating multi-criteria decision techniques with geographic information systems: a case study in Naqadeh, Iran.

Sanitary landfill is still the most significant and reasonable and the least expensive waste disposal method. The process of selecting a landfill site with minimal adverse effects on the environment is a complex task, in which numerous criteria need to be taken into account. In the present research, the AHP (analytical hierarchy process) and TOPSIS (technique for order of preference by similarity to ideal solution) models were used to weigh the layers and prioritize the identified regions, respectively. In the present study, the following criteria were considered: (1) environmental criteria consisting of groundwater depth and distance from rivers, streams, and wetland/dam/lake; (2) physical criteria consisting of geology, slope percentage, distance from faults, heights, soil depth, and aspect; (3) social-economic criteria including the subcriteria land uses and distance from urban centers and villages; and finally, (4) access factors with the subcriteria distance from roads and power lines. After the preparation phase, the maps corresponding to each subscale were weighed in GIS by means of AHP. To weigh the layers and evaluate the inconsistency rate of pairwise comparisons, the Expert Choice software, in which the AHP model can be run, was used. On the output map, 11 highly suitable areas for landfill were identified via the integration of layers and the identified options and were ranked using the TOPSIS technique and five secondary criteria based on experts' views. Ultimately, area no. 12 was selected as the proposed site for the landfill in Naqadeh County. The results indicated that the combination of multicriteria decision-making models including AHP and TOPSIS can be properly utilized for the purpose of locating.

Efficiency score assessment of Iranian Plastic Industries

Iranian Plastic Industries (IPI) created the main role in generating and producing a variety of plastic commodities and goods for inhabitant's demands. IPI comprised a cluster of 21 industries regarding the initial screening of Iranian evaluator team in Environmental Impact Assessment (EIA) plan. The present research empirically examined a way to find the efficiency score of IPI. Data Envelopment Analysis (DEA) model was integrated with Additive Ratio ASsessment (ARAS) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to estimate the efficiency score for IPI. The findings were classified IPI into 2 classes pertaining to both TOPSIS and ARAS models supported with both weighing systems of Friedman and Kendall tests. Moreover, the results proved an independent DEA value for the TOPSIS and ARAS models.