Fuzzy Multicriteria Research Articles

Location Assessment of Jatropha Cultivation for Biofuel Production in Fars Province, Iran: A Hybrid GIS-Based Fuzzy Multi-criteria Framework

Location Assessment of Jatropha Cultivation for Biofuel Production in Fars Province, Iran: A Hybrid GIS-Based Fuzzy Multi-criteria Framework

Ranking of Independent and Dependent Fuzzy Numbers and Intransitivity in Fuzzy MCDA

Ranking of fuzzy numbers (FNs) is a key stage within fuzzy multicriteria decision analysis (FMCDA). However, the influence of FNs dependence on their ranking, including ranking alternatives within FMCDA, has not been studied yet. In this article, for studying such an influence, the widely used defuzzification-based fuzzy ranking methods, centroid index, and integral of means, along with their modifications, which are pairwise comparison defuzzification ranking methods, are explored. The authors argue that classical defuzzification ranking methods are intended to deal with independent FNs, whereas their modifications may be used for ranking of dependent FNs. It is provided a proof in which, pairwise comparison Yuan’s and defuzzification integral of means ranking methods, are equivalent when ordering independent and can differ when ordering dependent FNs; at the same time, Yuan’s and modified integral of means ranking methods are equivalent when ordering both independent and dependent FNs. Intransitivity of the two modified ranking methods when ordering dependent FNs as well as intransitivity of alternatives in FMCDA for fuzzy multiattribute value theory (FMAVT) as an example is proved. The distinctions in ranking of dependent FNs by all ranking methods under consideration are explored through ordering alternatives within FMAVT. For this, a real-life case study is considered, and the distinctions in ordering alternatives by classical and modified ranking methods are demonstrated. Statistical analysis of distinctions in ordering alternatives by FMAVT with different ranking methods is implemented with the use of Monte–Carlo simulation. The significance of distinctions for the choice and ranking multicriteria problems, as well as for justification of utilizing ranking methods under consideration in FMCDA, is discussed.

Assessing the Best Supplier Selection Criteria in Supply Chain Management During the COVID-19 Pandemic.

In the last 10 years, organizations and researchers have recognized the importance of sustainable supply chain management (SSCM) because of the consumers, -profit and non-profit organizations, laws and regulations, and consumer social and corporate responsibilities. Supplier selection, environmental effects such as social cooperation, and other SSCM programmes, can all help to achieve the “triple bottom line (TBL)” of economic, environmental, and social advantages. Sustainable supplier selection (SSS) and firm performance are important factors in supply chain management (SCM). Organizations will traditionally consider a new framework when evaluating SSS performance to obtain all-encompassing criteria/sub-criteria of the sustainability index by encapsulating sustainability. This paper compiles 12 subcriteria for three sustainability pillars, namely economic, environmental, and social performance. Despite the fact that many articles on SSS and evaluation were published during COVID-19, there seems to be little research on sustainability issues to date. The goal of this study is to suggest a fuzzy multicriteria approach to SSCM planning. Additionally, using the TBL method, the problem of determining a current model for SSS in the supply chain was investigated. The linguistic value of the subjective preference of experts is represented by triangular fuzzy numbers. Fuzzy TOPSIS (technique for order preference by similarity to ideal solution) is proposed to use standard weights to rank SSS for qualitative performance evaluation. COVID-19, on the other hand, has a detrimental impact on SSS and company results. The organization’s performance suffers as a result of the COVID-19 shutdown. The proposed method is demonstrated using an example.

Implementasi Fuzzy Multi Criteria Decision Making Pada Seleksi Beasiswa Bank Indonesia

The Bank Indonesia Scholarship is a scholarship provided by Bank Indonesia for students at various universities, one of which is UIN Maulana Malik Ibrahim Malang. In the scholarship selection process, there are several criteria that affect the graduation of prospective scholarship recipients. However, often the process is not transparently. So a calculation method is needed, one of which is using Fuzzy Multi Criteria Decision Making (FMCDM). With FMCDM it can help to get an accurate and optimal decision on scholarship recipients. The FMCDM process begins with collecting information related to scholarships, scholarship applicants, and a set of criteria that will be used for consideration of scholarship acceptance. The set of criteria consists of 11 criteria, namely, Academic Achievement Index (GPA), international level achievement, national level achievement, provincial level achievement, district/city level achievement, father's occupation, mother's income, number of family dependents, house area, land and building tax, as well as electricity bills. The next step is to evaluate the fuzzy set by aggregating the weight of the criteria and the degree of compatibility of each alternative with the criteria. The aggregation result is called the fuzzy fit index which consists of 3 values, namely, the y value which represents the lower limit of the aggregation result, the q value which represents the middle limit, and the z value which represents the upper limit value. The three values are ranked using a ranking method for fuzzy numbers with a degree of optimism. So that the total integral value for each alternative will be obtained, which will be the decision in accepting the scholarship. From the results of the FMCDM, there is a ranking of decision alternatives from the highest priority to the lowest in determining scholarship acceptance.

Evaluation of Artificial Intelligence Models and Wireless Network Applications for Enterprise Sales Management Innovation under the New Retail Format

Enterprise sales are distinct from other types of technology sales. It refers to the procurement of big contracts that involve long sales cycles, multiple decision-makers, and a higher level of risk when compared to traditional sales. It has its very own way of doing the decision-making process. In the current age of Internet technology, almost every field has adapted or upgraded to Artificial Intelligence (AI) technology. Likewise, enterprise sales also use this vibrant technology to enrich the sales representatives’ work. It does not mean that it affects the employees’ jobs, but it makes them much more manageable. The New Retail Format is the concept of selling products through the blending of contexts of online and offline modes. Also, enterprise sales management defines the management of product sales in business-to-business (B2B) transactions. In this research, Fuzzy Multicriteria Decision-Making is used by the customer to choose various products in an enterprise sales store. Additionally, Particle Swarm Optimization is utilised in this application to monitor the stock (product) availability and sales of the available products between two larger organizations. In this article, the proposed model incorporates AI and Wireless Sensor Networks (WSN) for enterprise sales under a new retail format. In this research, Fuzzy Multicriteria Decision-Making with a Particle Swarm Optimization Algorithm is implemented to analyze the process of enterprise sales. The proposed algorithm is compared with the existing fuzzy clustering method. From the result, it is observed that the proposed algorithm has achieved 99.78%, whereas the existing system has given only 93.46% of accuracy.

Combining life cycle sustainability assessment and fuzzy multicriteria decision making method for prioritizing the flare technologies in the oil, gas, and chemical plants

AbstractLife cycle sustainability assessment (LCSA) of flare technologies can assist the stakeholders/decision‐makers to choose the most sustainable flare technology in life cycle outlook among multiple options. This article purposes in developing a framework of life cycle sustainability decision‐support for prioritizing the flare technologies by integrating the LCSA concepts and fuzzy multicriteria decision making (MCDM) method. A novel fuzzy MCDM (FMCDM) technique that can handle linguistic variables in the decision‐making matrix was progressed by integrating SWARA–WASPAS approach and fuzzy evaluation (fuzzy SWARA–fuzzy WASPAS). Using fuzzy SWARA is obtained the weights of the metrics for LCSA and then, fuzzy WASPAS is employed to prioritize the alternatives with considering the metrics. Finally, the findings of fuzzy SWARA show the “Production cost,” having the topmost weight with value of 0.5094, is the foremost metric that overshadows the choice of suitable and sustainable flare technology. The results obtained from the fuzzy WASPAS suggest that “Steam‐assisted flare,” is the highest prioritized and thus, the most significant alternative to employ flare technology in oil, gas, and chemical plants. The results indicate that combining LCSA and MCDM can effectively rank industrial systems and equipment under data uncertainties.

A novel MCDM model for warehouse location selection in supply chain management

The present investigation reveals a novel method for the evaluation of warehouse location for leagile supply chain entailing Fuzzy Multi Criteria Analysis (FMCA). An attempt has been made to apply the concept of decision theory for selecting the warehouse under contradictory criteria. Aggregate Modified Weighted Value (MWV) of normalized score of alternative is determined to evaluate Benefit Cost Ratio (BCR) which is considered as the warehouse selection index. The proposed algorithm is illustrated with a suitable numerical example to adjudge its desirable importance in capability and practicability. It also ensured that the achieved result clearly matches with those of previous research works. Finally, sensitivity analysis has been carried out that justify and supports the application of proposed algorithm in finding the most favorable outcome to the selection problem of warehouse location.

Supplier selection by integrated IFDEMATEL-IFTOPSIS Method: A case study of automotive supply industry

Selecting the best supplier emerges as a crucial subject for all sectors to achieve long term collaborations in supply chains. This study object to select the most suitable supplier for a company engage in activities in the automotive supply industry. For this purpose, a five-stage Intuitionistic Fuzzy Multi-Criteria Decision Making (IFMCDM) model is conducted. Firstly, decision criteria are defined by literature research and expert group opinions. Secondly, the importance weights of these criteria are obtained by IF Decision Making Trial and Evaluation Laboratory (IFDEMATEL). Followingly, the most suitable supplier is assessed by IF Technique for Order Preference by Similarity to Ideal Solution (IFTOPSIS). In the fourth stage, Sensitivity Analysis is utilized to analyze the effect of differentiation in criterion. Lastly, a comparative analysis is carried out. The results of the study has pointed that “Price” is the most important criterion in supplier selection and “Supplier 4” is the best alternative for this case. Main contribution of this study is to integrate IFDEMATEL-IFTOPSIS method for the first time in automotive supplier selection literature and propose a specific decision framework. In addition, proposed model is found robust and valid.

Process Based Failure Mode Analysis with Fuzzy Multi Criteria Decision Making Methods in Supply Chain Risk Management

Günümüzde; doğal afetlerin artması, teknolojinin hızla gelişmesi, ürün ömrünün kısalması, maliyetlerin artması, politik sebepler, arz ve talepteki belirsizlikler sonucu giderek artan tedarik zinciri riskleri ile karşılaşılmaktadır. İşletmeler rekabet avantajı sağlayabilmek, müşteri beklentilerini karşılayabilmek, sektörde pazar paylarını artırabilmek ve sürdürülebilirliklerini koruyabilmek için tedarik zinciri risklerini sistemli bir şekilde yönetmek durumundadırlar. Çalışmada, iklimlendirme ve ısıtma sektöründeki bir firmanın talep planlama sürecinde oluşan hatalar analiz edilmiştir. Bu çalışmada amaçlanan; Süreç HTEA (Hata Türü ve Etkileri Analizi) yönteminin zayıf yönleri sebebiyle, risk analizine Bulanık SWARA-Bulanık COPRAS tabanlı süreç aşamalı yeni bir yaklaşım getirmektir. Süreç HTEA yönteminin, alanında uzman karar vericilerin bilgi ve tecrübelerini değerlendirmelerde göz önüne alamaması şeklindeki zayıflıklarını iyileştirmek hedeflenmiştir. Bu amaçla, risk analizi için Bulanık SWARA-COPRAS tabanlı süreç aşamalı ÇKKV (Çok Kriterli Karar Verme) modeli önerilmiştir. Kriterlerin önem ağırlıklarını belirleyebilmek için Bulanık SWARA yöntemi, hataları sıralayabilmek için Bulanık COPRAS yöntemi kullanılmıştır. Bu yönteme göre, en önemli hataların; “HT-1: Talep rakamlarının eksik veya yanlış olması sonucu eksik üretimin S&OP (Satış ve Operasyon Planlama) toplantısında farkedilmesi” ve “HT5:Talep rakamları belirlenirken master datanın eksik tanımlanması sonucu eksik üretimin S&OP toplantısında fark edilmesi” olduğu tespit edilmiştir. İlerleyen çalışmalarda, risk analizlerinin etkinlikleri benzer yaklaşımlarla değerlendirilebileceği ve karar destek sistemlerine entegre edilerek mevcut veya gelecek senaryoların analizinde kullanılabileceği öngörülmektedir.

Selecting the Best Materials in the Manufacture of Automotive Polymer Parts with a Fuzzy Multi-Criteria Decision Approach

Selecting the Best Materials in the Manufacture of Automotive Polymer Parts with a Fuzzy Multi-Criteria Decision Approach

Location of Emergency Escape Ramps on Two-Lane Rural Highways Based on the Fuzzy Multicriteria Decision-Making Method

Today, the lack of practical research is one of the most important concerns worldwide, and location, which is an important issue in most projects, has received less attention from experts. In this study, the location criteria of emergency escape ramps were examined, and according to the Myers formula, the temperature-distance diagram along the route was obtained. Also, the speed of vehicles entering the escape ramp was examined according to the American Association of State Highway and Transportation Officials (AASHTO) in the proposed options that were obtained from the experts. Then, 3 general criteria and 16 subcriteria were classified, and finally, the importance of criteria was examined by the fuzzy analytic hierarchy process (F-AHP), and the high-priority options were illustrated using the fuzzy technique for order performance by similarity to ideal solution (F-TOPSIS). The proposed options were evaluated and prioritized for an emergency escape ramp on the two-lane rural highways of Salavat Abad village pass of Sanandaj city, Kurdistan Province, Iran. The results showed that the technical criteria with more than 69% among the general criteria and subcriteria of the percentage of longitudinal slope, longitudinal slope length, and vehicle design speed were the most important factors influencing the location of an emergency escape ramp. Moreover, among the proposed options, the four options 3, 4, 5, and 6 had the highest score, and option 6 (Kurkur turn (2)) was identified as the most priority location for implementing the emergency escape ramp.

An improved fuzzy multi-criteria algorithm for optimizing concentrated solar power (CSP) hybridized systems based on pythagorean fuzzy set

In concentrated solar power (CSP) hybridized systems, the selection of solar-hybrid power plants (SHPP) is very important, especially when the selected criteria and performance indicators are fuzzy and uncertain. The multi-criteria intuitionistic fuzzy decision-making method for selecting SHPP has been widely studied. Thus, the purpose of this paper is twofold. Firstly, we present the improved version of the Cavallaro et al., [2018]’s method. Improvement aspects include formulas expression, calculation data, intuitionistic fuzzy matrix, entropy, weights and the weighted correlation coefficient. After the improvement, the ranking result of the various alternatives (ISHCC-1, ISHCC-3, ORC-1, ST-1, ORCREC-3, PT-3, PART-1, PART-3) is changed from “OREREC-3 ≻ PART-3 ≻ ISHCC-3 ≻ ST-1 ≻ ORC-1 ≻ ISHCC-1 ≻ PT-3 ≻ PART-1” to “OREREC-3 ≻ PART-3 ≻ ISHCC-3 ≻ ST-1 ≻ ORC-1 ≻ ISHCC-1 ≻ PART-1 ≻ PT-3”. Secondly, an improved fuzzy multi-criteria algorithm for optimizing concentrated solar power (CSP) hybridized systems based on Pythagorean fuzzy set is presented. Where, a new weighted correlation coefficient based on Pythagorean fuzzy set is proposed. On the one hand, the effectiveness of the proposed method is demonstrated by comparing with the different methods in the medical diagnosis application, which shows that the new method is as efficient as the other methods. On the other hand, we use the proposed method to re-rank differ solar power hybridized systems with the purpose of strengthening the ranking results. The re-ranking results we get are still: OREREC-3 ≻ PART-3 ≻ ISHCC-3 ≻ ST-1 ≻ ORC-1 ≻ ISHCC-1 ≻ PART-1 ≻ PT-3. It further indicates that the modified results given in this paper are correct. Furthermore, the proposed new sorting method based on Pythagorean fuzzy set is effective and reasonable. The refinement will help readers understand Cavallaro et al., [2018] well, and then apply intuitionistic/Pythagorean fuzzy multicriteria algorithm in related issues better.

Spherical Fuzzy Multicriteria Decision-Making Model for Wind Turbine Supplier Selection in a Renewable Energy Project

The Vietnamese government has decided to use and promote the development of more renewable energy sources, particularly wind energy. When implementing a wind energy project, choosing a wind turbine supplier is an important decision and investors must find the optimal supplier through evaluating many qualitative and quantitative criteria that affect each other symmetrically. Therefore, the process used for selecting a wind turbine supplier in wind power projects is a multi-criteria decision-making process. Many approaches have been applied for this decision process, some of which are based on multicriteria decision-making (MCDM) methods, whether applied individually or in combination with other MCDM models. In this study, the researchers proposed a decision-making model based on spherical fuzzy sets for wind turbine supplier selection in wind power energy projects. In this paper, Vietnam is used as a case study. The recommended turbine suppliers for installations can finally be generated after the calculations in the final stage of this research. The contribution of this research is developing a fuzzy MCDM model for suitable turbine suppliers in wind power energy projects. The results of this study can be used as references for experts in deciding on a suitable wind turbine supplier in other countries as well as in other renewable energy projects.

Geographical information system based fuzzy multi criteria analysis for sustainability assessment of biomass energy plant siting: A case study in Queensland, Australia

Biomass energy has huge potential in helping to achieve a renewable energy target to combat climate change. Many countries like Australia have huge potential for biomass energy supply from second generation biomass resources, however, the limited knowledge on the potential of these biomass resources could be a barrier to its uptake. This study developed a geographical information system based fuzzy multi criteria analysis (GIS based Fuzzy-MCA) to identify and prioritise the suitability of biomass energy plant sites for the sustainable use of biomass. The analysis was carried out in Queensland, Australia as a case study, demonstrating the potential of multiple biomass types for multiple products (thermal energy and bioelectricity supply). Using local sustainability constraints and criteria, the study identified potential biomass energy plant (57) sites in the East, South-East and North-West regions of the state where there are vacant lands and required infrastructure. Moreover, the high-resolution assessment of sustainably available biomass can have a significant impact on suitability of the location and the plant capacity. The potential biomass energy plants could generate electricity satisfying a substantial portion of Australian bioelectricity goals and mandates. The methodology could further be used in national-scale assessment, considering biomass incentive programs and government policies to maximise public benefit and private investment.

A Fuzzy Multicriteria Group Decision Making Approach for Evaluating and Selecting Fintech Projects

The use of financial technologies (Fintech) has increased recently due to their support to financial institutions in managing their financial operations and achieving competitive advantages. Even though there are several benefits with Fintech development and implementation, selecting the most suitable Fintech project can be complex. This is due to the involvement of numerous decision makers, the conflicting nature of multiple evaluation criteria, and fuzzy data derived from imprecise judgments of qualitative performance ratings. Interval-valued based intuitionistic fuzzy numbers are used to deal with the inherent vagueness and imprecision of the evaluation process. An algorithm based on an interval-valued intuitionistic fuzzy weighted geometric (IIFWG) and the concept of ideal solutions is developed. As a result, the most suitable Fintech project alternative can be selected across all evaluation criteria. To demonstrate the effectiveness of the approach, a Fintech project selection problem is presented.

Hybrid Fuzzy Multi-Criteria Analysis for Selecting Discrete Preferable Groundwater Recharge Sites

This study proposes a hybrid fuzzy multi-criteria methodology for the selection of the most preferable site for applying managed aquifer recharge (MAR) systems by utilizing floodwaters. The use of MAR can increase water resources for later water utilization in case of drought. In this multi-criteria problem, seven recharge sites are under consideration, based on nine criteria, aiming to make a final list of their relative ranking. A fuzzy analytic hierarchy process (FAHP) based on the logarithmic fuzzy preference programming (LFFP) method is used to determine the weights of criteria. LFFP is an optimization-based method that produces a priority vector from a fuzzy pairwise comparison matrix. Furthermore, fuzzy inference systems (FIS) based on the Mamdani approach are used to estimate the rating of each alternative with respect to the criterion examined, and then the final evaluation of the alternatives is obtained. A FIS is a fuzzy if–then rule-based system where the experts’ qualitative knowledge is translated into numerical reasoning for each individual criterion. The proposed methodology is applied in the aquifer system of the agricultural plain located to the southeast of the city of Xanthi in the Prefecture of Xanthi, NE Greece.

An Adaptive Fuzzy Multi-Criteria Model for Sustainability Assessment of Sugarcane Agroindustry Supply Chain

Supply chain sustainability assessment is key to maintaining and improving the performance of agroindustry supply chains, particularly in sustainable agroindustry development. The assessment of agro-industrial supply chain performance is a complex and dynamic process. Hence, there is a need for an adaptive fuzzy multi-criteria sustainability assessment model as an alternative method of analysis and improvement. This study aimed to design an adaptive fuzzy multi-criteria sustainability assessment and improvement model for the sugarcane agroindustry supply chain. In this study: (1) a fuzzy inference system (FIS) was developed to assess the performance of the sustainability dimensions. This study proposed 24 indicators for four dimensions: economic, social, environmental, and resource. (2) An adaptive neuro-fuzzy inference system (ANFIS) is designed to aggregate the overall supply chain sustainability performance. (3) The proposed fuzzy multi-criteria assessment model was compared with the common multidimensional scaling (MDS) and linear models. This study proved that the proposed synthesis of the FIS and ANFIS models is powerful and adaptive for evaluating supply chain sustainability and providing accurate results. (4) The strategies to improve sustainability performance were developed using the cosine amplitude method (CAM). The proposed model determined that the overall supply chain sustainability value was 68.58%, which was almost sustainable. Several strategies have been suggested to improve sustainability performance, including maintaining the sugarcane supply by strengthening the partnership program and improving the mill’s overall recovery, followed by factory revitalization or new factory investment.

Fuzzy Multi-Criteria Decision Making for Solar Power Plant Location Selection

Vietnam is one of Southeast Asian countries with a rapid GDP growth rate, ranging from 6.5% to 7% annually, leading to an average increase in energy demand of 11% per year. This demand creates many new opportunities in the energy industry, especially renewable energy, to ensure sustainable development in the future for the country with applications of solar energy growing at the present, and other opportunities to expand in the future. In Vietnam, thanks to favorable weather, climate, terrain characteristics and many preferential support policies, there are many great opportunities in the field of solar energy exploitation and application. Location selection is an important problem in all renewable energy projects. Therefore, the author proposed a fuzzy Multi-criteria Decision-Making Model (MCDM) model for solar power plant location selection in this study, and as a result, location 5 is the optimal solution. The contribution of this study is to propose a MCDM for solar power plant location selection in Vietnam under fuzzy environmental conditions.

A novel methodology for portfolio selection in fuzzy multi criteria environment using risk-benefit analysis and fractional stochastic

<p style='text-indent:20px;'>This article proposes an efficient approach for solving portfolio type problems. It is highly suitable to help fund allocators and decision makers to set up appropriate portfolios for investors. Stock selection is based upon the risk benefits analysis using MADM approach in fuzzy environment. This sort of analysis allows decision makers to identify the list of acceptable portfolios where they can assign some portions of their asset to them. The purpose of this article is two folds; first, to introduce a methodology to select the list of stocks for investment purpose, and second, to employ a stochastic fractional programming model to assign money into selected stocks. This article proposes a hybrid methodology for finding an optimal or new optimal solution of the problem. This hybrid approach considers risks and benefits at the time of stocks prioritization. This is followed by solving a fractional programming to determine the percentages of the budget to be allocated to stocks while dealing with two sets of suitable and non-suitable stocks. For clarification purposes, a sample example problem is solved.</p>

Customer Satisfaction and Perception towards Service Quality by using Fuzzy Multi Criteria Decision Making Model (FMCDM)

The era of developing economy, banks need a multi-channel service platform. Technological advances are forcing banks to their multi-client service strategies to gain a competitive global scenario. This study examines how perceives service quality and satisfaction drives MCDM analysis in scaling at selected commercial banks. The current study enables the banks   usage   and implications of SERVQUAL to measure the Customer Satisfaction and Perception. Emergence of several banks clearly understands the needs of the customers and they are eager to attract a new customer and they also want to keep the existing customer which is very important to survive in the economy. This has led to increased competition among globalised banks. Finally, the banks focused on     inexpensive of services. This study is especially useful for business, shareholders and stakeholders.