Vise Kriterijumska Optimizacija I Kompromisno Resenje Research Articles

Integer Code Series Enhanced IT2 Fuzzy Decision Support System With Alpha Cuts for the Innovation Adoption Life Cycle Pattern Recognition of Renewable Energy Alternatives

This study aims to evaluate the innovation adoption performance of the renewable energy alternatives. Within this context, a new model is created that consists of two different stages. Firstly, the decision combinations of innovation adoption life cycle patterns are identified by considering integer code series. On the other side, in the second stage, the innovation adoption life cycle performance of the renewable energy alternatives is ranked. In this framework, interval type-2 (IT2) fuzzy technique for order preference by similarity to ideal solution (TOPSIS) methodology is taken into consideration based on alpha cut levels. Moreover, a comparative evaluation is also conducted by considering IT2 fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). It is identified that the analysis results are quite coherent and reliable. The findings demonstrate that solar energy is the most appropriate renewable energy type to make innovation. Additionally, wind and geothermal energies are also other significant renewable energy types that have a great innovation potential. However, it is also concluded that biomass and hydroelectric energy have lower importance in comparison with the others. Another important point is that the ranking results are quite similar for different alpha cuts. This condition indicates that the analysis results are coherent and reliable. It is obvious that making investment to solar energy alternatives provides opportunity to adopt technologic innovation more easily. Therefore, it is recommended that investors should give priority to solar energy projects so that it can be more possible to increase the efficiency and the profitability of the investments.

An Integrated Methodology for Selecting and Evaluating Sustainable Suppliers in Supply Chains

Business companies have highlighted the significance of greening and sustainability in their supply chain via supplier selection as a result of increasing consumer awareness and ecological demands from markets and different stakeholders. As a result, from the viewpoint of an organizational supply chain, a systematic and sustainability-focused assessment methodology for supplier selection is required. This paper offers a framework for evaluating sustainable supplier selection by combining an Analytical Hierarchy Process (AHP) with Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a multi-criteria optimization and compromise solution method. Initially, literature and expert views established 22 sustainable supplier selection criteria and three aspects of criteria (economic, environmental, and social). To illustrate the applicability of the suggested framework, a real-world example of an automotive business in India is presented. The top five sustainable supplier selection factors, according to the results, are “Environmental costs“, “Quality of product“, “Price of product“, “Occupational health and safety systems“, and “Environmental competences“. Furthermore, among the five sustainable supplier options, supplier number three received the highest ranking. The research provided in this article may assist managers and business professionals in not only identifying key supplier selection criteria, but also in evaluating the most efficient supplier for supply chain sustainability and market competitiveness. To evaluate the proposed framework’s resilience, a sensitivity analysis is performed.

TRIZ-Based Green Energy Project Evaluation Using Innovation Life Cycle and Fuzzy Modeling

This study evaluates theory of the solution of inventive problems (TRIZ)-based green energy project network based on innovation life cycle. In this context, TRIZ-based combinations are obtained by integer patterns for green energy projects. In the next phase, activity priorities of TRIZ-based principles are measured for green energy projects with Pythagorean fuzzy (PF) technique for order preference by similarity to ideal solution (TOPSIS). Finally, project evaluation review technique (PERT) and PF decision making trial and evaluation laboratory (DEMATEL) approaches are taken into consideration to score the green energy projects based on innovation life cycle using inventive problem-solving principles. TRIZ-based principles are also ranked by using Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Additionally, all calculations have also been made with Spherical fuzzy (SF) sets in addition to the PF sets. It is concluded that the analysis results are quite reliable. The main contribution of this study is that innovative strategies are identified for green energy investment projects with a novel methodology. The findings indicate that dynamicity and transformation of properties play a crucial role in this process. Therefore, green energy investors should closely follow technological developments in this area and the products used in green energy investments should be easily adapted to these developments. Additionally, the principal of prior action should be considered to reduce the costs instead of periodic action. It is obvious that the necessary controls should be made before the project starts to increase the efficiency and productivity.

A sustainability evaluation framework for WET-PPP projects based on a picture fuzzy similarity-based VIKOR method

Abstract This paper aims to construct a sustainability evaluation framework based on the extended VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method under a picture fuzzy environment. First, a sustainability evaluation index system for water environment treatment public-private-partnership (WET-PPP) projects is constructed from the perspectives of the economy, engineering, environment, management, and society, including five criteria and 20 sub-criteria. The constructed index system considers engineering sustainability and management sustainability, and can thus more comprehensively evaluate the “sustainability” of the project and meet the requirements of the new economic environment. Second, a corresponding method for the sustainability evaluation of WET-PPP projects is proposed based on the picture fuzzy similarity-based VIKOR method. The main advantages of the proposed method include the following: (1) the sustainability evaluation process for WET-PPP projects involves linguistic terms and picture fuzzy numbers (PFNs), which can not only more comprehensively describe the uncertainty of human cognition and decision-making processes in the form of positive, neutral, and negative membership functions, but can also reduce the difficulty for decision-makers (DMs) to provide evaluation information; (2) the proposed evaluation method combines picture fuzzy similarity and the traditional VIKOR method, and can therefore not only obtain compromise solutions but can also ensure the stability and feasibility of the evaluation results. Finally, a case study of WET-PPP projects in China is provided to testify the feasibility and effectiveness of the constructed framework. The results indicate that the proposed framework can improve the accuracy of decision-making and can be applied for handling evaluation problems.

Aggregation operators and VIKOR method based on complex q-rung orthopair uncertain linguistic informations and their applications in multi-attribute decision making

Complex q-rung orthopair uncertain linguistic set (CQROULS) is a combination of complex q-rung orthopair fuzzy set (CQROFS) and uncertain linguistic variable set (ULVS) as a proficient technique to express uncertain and awkward information in real decision theory. CQROULS contains uncertain linguistic variables, truth and falsity grades, which gives extensive freedom to decision makers for taking a decision as compared to CQROFS and their special cases. In this article, a new concept of fuzzy set, called CQROULS using CQROFS and ULVS is explored, and this can examine the qualitative assessment of decision makers and gives them extensive freedom in reflecting their belief about allowable truth grades. Based on the established operational laws and comparison methods for CQROULSs, the notions of complex q-rung orthopair uncertain linguistic weighted-averaging aggregation operator and complex q-rung orthopair uncertain linguistic weighted geometric aggregation operator are explored. Some special cases and the desirable properties of the explored operators are also established and studied. Additionally, the notion of VIseKriterijumska Optimizacija I KOmpromisno Resenje (VIKOR) method based on CQROULSs is explored, with the help of a numerical example, it is verified and also its comparative study is established. Moreover, based on the above analysis, we establish a method to solve the multi-attribute group decision making problems, in which the evaluation information is shown as CQROULNs. Finally, we solve some numerical examples using some decision making steps and explain the verity and proficiency of the explored operators by comparing with other methods, the advantages and graphical interpretation of the explored work are also discussed.

An Extended VIKOR Method Based on q-Rung Orthopair Shadowed Set and Its Application to Multi-Attribute Decision Making

In the multi-attribute decision making (MADM) process, the attribute values are sometimes provided by experts or the public in the form of words. To model the linguistic evaluation more accurately, this paper proposes the q-rung orthopair shadowed set (q-ROSS) to represent attribute values and extends the VIKOR (VIsekriterijumska optimizacija i KOmpromisno Resenje) method to solve MADM problems in the q-ROSS context. First, we propose the q-ROSS to express evaluation information. Some basic operation rules and distance measures are investigated accordingly. When the amount of data is large, the left and right endpoints of the collected interval numbers will obey symmetric normal distribution. Secondly, based on the normal distribution assumption, the collected data intervals are mapped to shadowed sets through a data processing approach. Furthermore, we extend the VIKOR model to tackle the MADM problem where the evaluation values are expressed by q-rung orthopair shadowed numbers. A location selection problem verifies the practicability of our method, and the effectiveness and superiority of the presented approach are reflected through comparative analysis.

Development of a multi-criteria decision-making model for comparing the performance of Turkish commercial banks

PurposeIn this study, financial performance evaluation model is developed for banks aims to measure and compare the performances of banks based on their financial ratios.Design/methodology/approachRegression-AHP (Analytic Hierarchy Process)-VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje) integrated methodology is used. First, a literature review is done to find various bank performance measurement models with their financial metrics being compared. Then, pair-wise comparison matrices are used to find the relative weights of criteria (financial ratios) and finally VIKOR method is used to rank the banks.FindingsIt is believed that an AHP-based VIKOR framework helps to take up the explicit account of multi-criteria decision making (MCDM) methodologies in decision making and for selecting the best bank in the Turkish economy.Research limitations/implicationsIn this paper, only selected financial ratios are used and analyzed for the multi-criteria decision-making (MCDM) method.Originality/valueThe systematic solution procedure of performance evaluating the banks helps the decision-makers to carry out performance evaluation studies for improving economic and managerial performance. This comparative study and analysis of bank performance using the regression-AHP-VIKOR combined model is presented for the first time. The authors have not become aware of any such studies in their literature review. This paper is an original framework of the application of the regression-AHP-VIKOR on the various financial performance metrics.

An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

With the expansion of urbanization caused by the growth of population and industrial activities, the urban/city and suburban areas are facing a variety of environmental threats. Although more research and urban policy has advocated and practiced the development of green infrastructure (GI) to support urban sustainable environment, the evaluation framework for the development of GI for promoting environmental sustainability is still insufficient. Moreover, the Analytic Hierarchy Process (AHP) commonly applied in published literature, makes an unrealistic assumption of independent relationships among dimensions/criteria in decision making for satisfying the real-world problem. Therefore, the purpose of this study is to construct the evaluation framework, including four dimensions and related ten criteria, using a new hybrid-modified multiple attribute decision-making (MADM) model for developing and improving the GI for promoting environmental sustainability. This MADM model is combined with three different methodologies of MADM, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for constructing the influential network relation map (INRM) to explore the complex influential inter-relationships and DEMATEL based on Analytic Network Process (DANP) for determining the influential weights with the VIse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating and presenting improvement strategies for six different GIs. The empirical study indicates that DEMATEL and DANP Results suggest that decision-makers should pay more attention to the improvement of Design (D4) and Materials (D2) in terms of dimensions when utilizing the GI to promote environmental sustainability. Because these dimensions are enhanced, Species (D1) and Energy (D3) will be improved in synchronization. From the perspective of criteria, five are key core criteria and need to be focused on first: increasing the green coverage rate (B9), utilizing sustainable materials (B4), using ecological engineering (B8), shaping species biodiversity (B1), and reducing energy consumption (B5). Modified VIKOR reveals that “grass swales” are a comparatively better choice among six GIs for promoting environmental sustainability toward achieving the aspiration level. Therefore, this MADM model is beneficial to provide a more convincing assessment framework and improvement strategies for the development of GI for promoting environmental sustainability. As a result, these modified MADM models can be shown more conveniently and reasonably than traditional methods such as traditional AHP or ANP method.

Assessing and Prioritizing the Climate Change Policy Objectives for Sustainable Development in Pakistan

The world is facing the observable and direct impacts of climate change in the shape of extreme weather events, irregular precipitation, glacial melt, sea-level rise, an asymmetric average temperature trends, higher oceanic temperatures, damage to natural ecosystems, and biodiversity. In 2015, collective wisdom stirred the global community to agree upon two unprecedented milestones in recent human history—the Paris agreement and sustainable development goals (SDGs). The twin global agreements set a platform for collective efforts to secure socio-economic and climatic sustainability. Pakistan also joined the board to put forth policy interventions for the mitigation and adaption of climate change risks to maintain symmetry between the environmental quality and economic development. The government of Pakistan (GOP) formulated the National Climate Change Policy (NCCP (2012)) and passed the Pakistan Climate Change Act (PCCA (2017)) to provide an impetus for the implementation of the NCCP. Yet, an appropriate assessment and prioritization of the objectives of the NCCP are indispensable for productive and effective policies to achieve the targets. This study serves this purpose by prioritizing the climate change policy objectives (CCPOs) based on symmetric principles, i.e., energy, transport, urban and town planning, industry, and agriculture as criteria, with 17 sub-criteria in total. The fuzzy analytical hierarchy process (AHP) results show that the energy sector is the most pivotal while implementing the NCCP. Energy production is the most critical area that needs mitigation policy intervention for shifting the energy mix of the economy from high-carbon to low-carbon energy. The fuzzy AHP analysis further revealed the railway, population and urbanization, air pollution, crop growing practices and techniques as the most important related to transport, urban planning, industry, and agriculture sub-criteria, respectively. The fuzzy VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis showed the ranking of the CCPOs from high to low through the integration of policies, institutional capacity building, water security, natural resource management, natural disaster management, environmental financial structure development, and social sector development. The findings of the present research would be helpful for experts and policymakers to re-examine the NCCP and put forth action plans to achieve sustainable climate and SDGs.

A robust decision making approach for hydrogen power plant site selection utilizing (R, S)-Norm Pythagorean Fuzzy information measures based on VIKOR and TOPSIS method

In recent years, there is a rapid development in the direction of hydrogen energy industry having primary involvement in automobile transportation fuel. Hydrogen is the most abundant element and serves as a perfect energy carrier. In general, choosing an appropriate hydrogen power plant site is a complex selection multi-criteria decision making (MCDM) problem which involves proper assessment of a location based on various essential criteria, decision maker's expert opinion and other qualitative/quantitative factors. In the present communication, we first incorporate (R,S)-Norm Pythagorean fuzzy entropy and respective discriminant measure in the VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM techniques and proposed the modified MCDM algorithms in two different stages. Further, the hydrogen power plant site selection problem has been dealt with proper matching of the laid down essential criteria under a wider sense of Pythagorean fuzzy information measures. Such measures have not been utilized in the study of site selection problems of the hydrogen energy resources. In view of the existing literature on the MCDM problems, comparative remarks including the sensitivity analysis and the advantages have been presented for providing the novelty of the proposed methodologies. The presented work proves to be an effective tool for handling the various similar types of selection problems with a desired consistency.

A Fuzzy VIKOR method to analyze the risks in lean manufacturing implementation

Lean manufacturing is a theory, widely identified to gain more profits, reduce waste, and deliver valued products for customers without harming productivity. Albeit, it is a lucrative business trick, but implementation possesses a massive hurdle for success in any organization. Therefore, for the successful implementation of a lean manufacturing system, the factors and the risks involved should be identified and eliminated. This research is a case study of such risks involved in the implementation of Lean Manufacturing system in medical equipment manufacturing firms located in the southern part of India. The identification of risks was made by a literature survey as well as inputs from industry experts and analysis of risk using MCDM methods like Fuzzy Nominal Group Method (NGM) and VIKOR (VIseKriterijumskaOptimizacija I KompromisnoResenje) methods. The outcome of this paper is a selection of the best medical equipment manufacturing firms among a list of firms, based on the implementation of a lean manufacturing system. The proposed outcome of this research work was verified with case companies, existing literature, and consultation with experts. Finally, a sensitivity analysis was used to validate the results from the above methods.

Using hybrid normalization technique and state transition algorithm to VIKOR method for influence maximization problem

Influence maximization problem is the procedure of attempting to identify a group of K nodes in a social network in order to maximize the dissemination of influence under certain influence models. Based on state transition algorithm (STA) and a multiple criteria decision making (MCDM) method called Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), a novel hybrid approach has been proposed to cope with the influence maximization problem in this paper. Firstly, an intelligent optimization paradigm called STA is introduced to obtain the most appropriate weights that are used to integrate the criteria of each alternative in the VIKOR method. Then, a hybrid normalization technique has been presented to allow the process of aggregating criterion with numerical and comparable data properly in this method. Several typical networks have been used to testify the effectiveness of proposed method and technique. Compared with other approaches, experimental results show that our approach can solve the influence maximization problem more effectively.

Z-number integrated weighted VIKOR technique for hazard prioritization and its application in virtual prototype based EOT crane operations

Hazard identification and its ranking is one of the foundation steps of safety management. Nowadays, failure mode and effect analysis (FMEA), a reliability analysis tool, is widely used to identify, assess, and rank hazards/failure events related to products, processes, and services because of its simplistic nature. Traditional FMEA focuses on computing the risk priority number (RPN) to rank the identified hazards based on three risk factors, occurrence (O), severity (S), and detectability (D) of a failure mode (FM). However, the traditional RPN method has been criticized because of its limitations in the assessment of hazards/failure events, weighting of the risk factors, and prioritization of the FMs. Furthermore, experts usually provide rating on the risk factors based on their expertise, which introduces impreciseness, uncertainty, and vagueness in the subsequent assessments. In this study, Z-number is used to capture the uncertainty and unreliability associated with experts’ evaluation. Also, the concept of objectivity is deployed along with subjectivity in the weight calculation of the risk factors in the information assessment process. Classic VIKOR (ViseKriterijum-ska Optimizacija I Kompromisno Resenje) method is also extended in Z-environment to rank the identified hazards by incorporating the concepts of maximum group utility and minimum regret. For the illustration purpose, we have applied our proposed method in virtual prototyping based EOT crane operations. Sensitivity analysis and comparative evaluation with the existing methods are also presented to validate our proposed method.

A New Decision Model Approach for Health Technology Assessment and A Case Study for Dialysis Alternatives in Turkey.

Background: This paper presents a generic Multi-Criteria Decision Analysis (MCDA) model for Health Technology Assessment (HTA) decision-making, which can be applied to a wide range of HTA studies, regardless of the healthcare technology type under consideration. Methods: The HTA Core Model® of EUnetHTA was chosen as a basis for the development of the MCDA model because of its common acceptance among European Union countries. Validation of MCDA4HTA was carried out by an application with the HTA study group of the Turkish Ministry of Health. The commitment of the decision-making group is completed via an online application of 10 different questionnaires. The Analytic Hierarchy Process (AHP) is used to determine the weights. Scores of the criteria in MCDA4HTA are gathered directly from the HTA report. The performance matrix in this application is run with fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), fuzzy Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and goal programming MCDA techniques. Results: Results for fuzzy VIKOR, fuzzy TOPSIS, and goal programming are 0.018, 0.309, and 0.191 for peritoneal dialysis and 0.978, 0.677, and 0.327 for hemodialysis, respectively. Conclusions: Peritoneal dialysis is found to be the best choice under the given circumstances, despite its higher costs to society. As an integrated decision-making model for HTA, MCDA4HTA supports both evidence-based decision policy and the transparent commitment of multi-disciplinary stakeholders.

Multi-response optimization of electrochemical micromachining on masked SS304

This paper investigates on electrochemical micromachining of woven fabric masked stainless steel SS304 using 0.5 mm copper tool electrode with sodium nitrate (NaNO3) Electrolyte. Investigation is carried out to express the performance measures of micro hole such as metal removal rate (MRR), taper angle (TA) and surface roughness (SR). The experimental plan is based on taguchi L16 orthogonal array. Various input process parameters such as voltage, duty ratio, rotational speed, feed rate of tool and electrolyte concentration are varied at four levels. Significant contributions by input process parameters for each output responses such as metal removal rate, taper angle and surface roughness are analysed using contour plots. It is evident that significant contribution to metal removal rate mainly depends on rotational Speed and feed rate of tool. Similarly, duty ratio and feed rate of tool are the significant contributors for both taper angle and surface roughness. Multi response optimization are done for the three output responses using VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to identify the significant process parameter. Performance score of VIKOR and TOPSIS proved that rotational speed of tool, feed rate and duty ratio are important parameters contributing significantly for precision of microfeatures. Both the multi response optimisation methods mutually concluded the best performance is achieved at voltage 21 V, duty ratio 80%, rotational speed of tool 600 rpm, feed rate of tool 0.8 μm s−1 and electrolyte concentration 0.2 M. The confirmation test showed an improvement of performance grade by approximately 0.245.

AN INTEGRATED MULTI-CRITERIA DECISION-MAKING FRAMEWORK FOR SUSTAINABLE SUPPLIER SELECTION UNDER PICTURE FUZZY ENVIRONMENT

Sustainable supplier selection (SSS) is an important part of sustainable supply chain management (SSCM). In this paper, an integrated multi-criteria decision-making (MCDM) framework, based on the picture fuzzy exponential entropy, and the VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method, is proposed to manage SSS problems. Firstly, the evaluation criteria of SSS, including economic, environmental and social, is established. This can be evaluated in the form of the actual data or linguistic terms provided by suppliers and experts respectively in an actual decision-making process. Then, according to the translated scales, all the evaluation information can be converted into picture fuzzy numbers (PFNs). Secondly, the picture fuzzy exponential entropy is defined. Moreover, based on the entropy’s minimization principle, the defined picture fuzzy exponential entropy is used to determine the weight of the SSS’s criteria. Thirdly, the extended VIKOR method, which combines the grey correlation coefficient, is utilized to select a suitable supplier. This method avoids the shortcomings of the traditional VIKOR method in data mining and solves the conflict between SSS criteria. Finally, the feasibility and effectiveness of the proposed integrated decision framework are verified by an experiment, as well as a sensitivity analysis and comparative analysis.

A comparison of multicriteria decision analysis techniques for determining beekeeping suitability

Over the past decade, the importance of the beekeeping activities has been emphasized in the field of biodiversity, ecosystems, agriculture, and human health. Thus, deciding correct beekeeping activities seems essential to maintain and improve productivity and efficiency. Due to this importance, considering the economic contributions of beekeeping to the rural area, the need for suitability analysis concept has been revealed. At this point, multicriteria decision analysis (MCDA) and geographical information system (GIS) integration provides efficient solutions to the complex structure of decision-making process for beekeeping activities. In this study, site suitability analysis for beekeeping via analytical hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), and vise kriterijumska optimizacija I kompromisno resenje (VIKOR) was carried out to increase honey productivity and compare MCDA techniques for Konya city in Turkey. Slope, elevation, aspect, distance to water resources, roads and settlements, precipitation, and flora criteria were included to determine suitability. The requirements, expectations, and limitations of beekeeping activities were specified with the participation of experts and stakeholders. The final suitability maps resulted from each method were validated with existing 117 beekeeping locations and Turkish Statistical Institute 2015 beekeeping statistics for Konya province. Considering existing beekeeper locations, AHP has 82%, VIKOR 88%, and TOPSIS 91% overlapping rates with the suitability maps. According to the correlation R values between total beekeeper count and suitability rates, VIKOR has 0.70, TOPSIS 0.68 and AHP 0.66.

Establishing a Sustainable Sports Tourism Evaluation Framework with a Hybrid Multi-Criteria Decision-Making Model to Explore Potential Sports Tourism Attractions in Taiwan

In recent years, the awareness of sustainable tourism has risen around the world. Many tourism industries combine sports to attract more customers to facilitate the development of the economy and the promotion of local culture. However, it is an important task to establish a comprehensive tourism evaluation framework for sustainable sports tourism. This study proposes a Multi-Criteria Decision-Making (MCDM) model to discuss the above issues, using the Bayesian Best Worst Method (Bayesian BWM) to integrate multiple experts’ judgments to generate the group optimal criteria weights. Next, the modified Visekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) technique is combined with the concept of aspiration level to determine the performance of sports attractions and their priority ranks. In addition, this study adds a perspective of institutional sustainability to emphasize the importance of government support and local marketing. The effectiveness and robustness of the proposed model is demonstrated through potential sports tourism attractions in Taiwan. A sensitivity analysis and models comparison were also performed in this study. The results show that the proposed model is feasible for practical applications and that it effectively provides some management implications to support decision-makers in formulating improvement strategies.

Novel Ensemble of MCDM-Artificial Intelligence Techniques for Groundwater-Potential Mapping in Arid and Semi-Arid Regions (Iran)

The aim of this research is to introduce a novel ensemble approach using Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR), frequency ratio (FR), and random forest (RF) models for groundwater-potential mapping (GWPM) in Bastam watershed, Iran. This region suffers from freshwater shortages and the identification of new groundwater sites is a critical need. Remote sensing and geographic information system (GIS) were used to reduce time and financial costs of rapid assessment of groundwater resources. Seventeen physiographical, hydrological, and geological groundwater conditioning factors (GWCFs) were derived from a spatial geo-database. Groundwater data were gathered in field surveys and well-yield data were acquired from the Iranian Department of Water Resources Management for 89 locations with high yield potential values ≥ 11 m3 h−1. These data were mapped in a GIS. From these locations, 62 (70%) were randomly selected to be used for model training, and the remaining 27 (30%) were used for validation of the model. The relative weights of the GWCFs were determined with an RF model. For GWPM, 220 randomly selected points in the study area and their final weights were determined with the VIKOR model. A groundwater potential map was created by interpolating the values at these points using Kriging in GIS. Finally, the area under receiver operating characteristic (AUROC) curve was plotted for the groundwater potential map. The success rate curve (SRC) was computed for the training dataset, and the prediction rate curve (PRC) was calculated for the validation dataset. Results of RF analysis show that land use and land cover, lithology, and elevation are the most significant determinants of groundwater occurrence. The validation results show that the ensemble model had excellent prediction performance (PRC = 0.934) and goodness-of-fit (SRC = 0.925) and reasonably high classification accuracy. The results of this study could aid management of groundwater resources and assist planners and decision makers in groundwater-investment planning to achieve sustainability.

Picture fuzzy normalized projection and extended VIKOR approach to software reliability assessment

An extended VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) method in group decision-making (GDM) setting is developed in this paper. The decision information is characterized by picture fuzzy number. A new GDM model is established and applied to software reliability assessment. First, this research finds that the current projection measure is not always reasonable in picture fuzzy setting. To solve this problem, a new normalization projection measure is developed in picture fuzzy setting. In addition, this research also finds that the most VIKOR-based GDM method requires a collective decision as a carrier to get an optimal solution. However, if a collective decision is aggregated by all the individual decisions, the positive and negative information might be canceled each other out in the decision process. To solve this problem, this paper proposes a direct VIKOR-based GDM method. The values of three VIKOR indexes are determined by the original decision matrices. The feasibility and practicability developed method in this work are illustrated by an example of software reliability assessment and some experimental analyses.