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Fuzzy Multiple Attribute Decision Making: Methods and Applications
Abstract
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... The first TOPSIS method was introduced by Cheng & Hwang [31], with reference to Ching & Yoon [32], to select the best options from a set of alternatives based on a set of criteria. In this method, the distance between the alternatives is calculated using the Euclidean distance formula. ...
... Step 5 The separation of each option from the PIS is calculated using Eq. (31). ...
... After identifying PIS and NIS using Eqs. (31) and (32), the distance of each alternative from PIS and NIS was estimated for all criteria. For example, distance S1 was calculated as follows: The distances between the other suppliers were calculated similarly, as shown in Table 14. ...
In this study, a new integrated scenario-based stochastic rolling-planning multistage logistics model is proposed to reduce overall logistics costs. To achieve this goal, two phases were considered in the model. In the first phase, a multi-criteria group decision-making model was developed to select a trustworthy supplier. In the second stage, the selected suppliers were integrated with other stakeholders to develop a rolling-planning-based logistics model using a variety of risky scenarios. Several risk factors including price variability, demand, and quality risks were considered in the model. By considering these risk factors, a new risk-embedded rolling-planning logistics method was established that regulates inventory, stock-out, and overstock problems by constantly controlling the production volume at the manufacturing site based on actual demands. In this model, the supplier's side material quality, price fluctuation risks, and customer-side demand risks were considered simultaneously. To evaluate the performance of the proposed model, a numerical example was set up, and the obtained results were compared with those of another model where fixed volume production and delivery approach was used instead of the rolling-planning approach. To verify the superiority and robustness of the proposed model, its performance was verified through a sensitivity analysis under different experimental conditions. The findings show that in a risk environment, the proposed model estimates lower logistics costs of 2697648.00 units compared to another model whose costs were 2721843.00 units.
... Afterward, the triangular fuzzy value of each factor was established based on the evaluation values for the factors identified by professionals in various fields ( Fig. 1): µ A (x) = (L, M, U). In this study, the fuzzy set defuzzification method proposed by Chen and Hwang (1992) was used to calculate the left boundary value (L), the middle boundary value (M) and the right boundary value (U); finally, the total value was calculated. (T) A threshold value of 0.600 was set for the evaluation of the criteria. ...
... In this study, based on the collected evaluation values of the importance of the key factors for the development of culinary arts classes at rural B&Bs (Table 3), triangular fuzzy numbers were sequentially established, and the fuzzy sets of Chen and Hwang (1992) were used to defuzzify the triangular fuzzy numbers of the key factors identified by various catering and lodging-related professionals; the numbers were divided into left boundary values of defuzzification (μL), right boundary values of defuzzification (μR), and total values of defuzzification (μT). In this study, the triangular fuzzy number and the total value of defuzzification (μT) were calculated using the data collected through the FDM questionnaire. ...
The aim of this study is to establish the key factors for the development of cooking classes in Taiwan’s rural bed and breakfasts (B&Bs) to address the gaps in Taiwan’s research on this topic and contribute new knowledge to the development of Taiwan’s B&B industry. This study was conducted in two stages. In the first stage, the fuzzy Delphi method (FDM) was used to collect expert opinions and construct indicators; in the second stage, the analytic hierarchy process (AHP) was used to analyse the importance of indicators. The research results indicated that the most important factor for the development of cooking classes at rural B&Bs is “homestay management”, of which environmental hygiene and cleanliness are the most important indicators. This study fills the research gap related to gourmet and cooking tourism within the B&B industry, and the most notable contribution of this study is the identification of the key factors for the development of cooking classes at rural B&Bs. In addition, this study serves as a reference for the development of new business types in the B&B industry in Taiwan. The criteria of this study were evaluated by experts in various fields. Because the development of food tourism and cooking classes in Taiwan is still a novel topic, there may be many aspects that have not yet been explored, which is the most notable limitation of this study.
... Fuzzy set theory was developed to deal the fuzziness, qualitative, unstructured problems and uncertainty of the expert's judgement which is the outstanding component of vagueness governed by the human decisions [7,43,44,51]. A novel methodology for handling AHP for synthetic extent values is the use of extent analysis method and pairwise comparison scale of fuzzy AHP for triangular membership functions [10,37,38]. ...
... The standards of linguistic variables are shown in Table 1. Extreme importance( ) (7,9,11) (1 11, 1 9, 1 7 ⁄ ⁄ ⁄ ) ...
Cotton, the essential cash crop of India plays a predominant part in the agricultural and industrial enlargement of the world. The evolution of cotton plant begins with the germination of seed and its growth depends on the accessibility of temperature, soil moisture and oxygen. The desirable characteristics combined in cotton make no other fiber to duplicates its value. There are beyond 75 critical diseases leads to the substantial destruction and economic losses in cotton crop. Premature analysis of the cotton plant diminishes the disease, results in the significant enhancement in the superiority of the product. Massive yield of cotton crop is vanished each year due to fast incursion by insects and pests. Verticilium wilt, grey mildew, leaf spot and leaf blight are some of major cotton disease in cotton plant which extremely affects the productivity. This research discusses the multi criteria decision making evaluation tool to identify the major disease causing factors of cotton crop. Fuzzy AHP, a Multi Criteria Decision making method (MCDM) is applied to impact the disease causing risk factors by determining the weights of the criteria. Moreover, a Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a ranking MCDM methodology has been applied to rank the alternatives. The outcomes and methods described in this research based on the derived criteria and sub criteria of risk factors will be a noble orientation in producing more perfect, active and efficient decision support tool for the farmers to identify and diagnose the risk factors during the cultivation of the cotton crop
... In the classical formulation of the group decision-making (GDM) problem [1,2], there is a set of alternatives X and a group of decision-makers (DMs), which express their opinions about the alternatives to reach a common decision. In a fuzzy formulation, the problem is to order the alternatives from the best to the worst by associating them with some preference degrees in the interval [0, 1]. ...
... In the classical formulation of the group decision-making (GDM) problem [1,2], there is a set of alternatives X and a group of decision-makers (DMs), which express their opinions about the alternatives to reach a common decision. In a fuzzy formulation, the problem is to order the alternatives from the best to the worst by associating them with some preference degrees in the interval [0, 1]. There are some different ways [3] to set preferences: • By utility values; • By ordering the alternatives from the best to the worst; • By using a preference relation. ...
The present paper investigated the aggregation of individual preferences into a group fuzzy preference relation for a fuzzy set of decision-makers (DMs). This aggregation is based on the Kemeny optimization scheme. It was proven that this group relation is a Type-2 fuzzy relation (T2FR). The decomposition approach was used to analyze the group T2FR. It is shown that the group T2FR can be decomposed according to secondary membership grades into a finite collection of Type-1 fuzzy relations. Each of them is a group fuzzy relation for a crisp set of DMs, which is the corresponding α-cut of the original fuzzy set of DMs. Illustrative examples are given.
... The Delphi method's decision-making process tends to emphasize the acquisition of a 'definitely viable option excessively. ' Drawing on Hwang and Yoon's work [14], the TOPSIS method is expounded upon in Chen and Hwang [15]. The fundamental principle is that the selected alternative should be the closest to the ideal solution and the farthest from the negative ideal solution. ...
This research investigates the impact of various pedagogical strategies on the learning performance of non-accounting major students, with a focus on the flipped classroom model. The study reveals that interactive teaching between educators and students emerges as the optimal solution, emphasizing the need for dynamic and participatory teaching methods to encourage active engagement. Additionally, the research suggests the importance of enhancing student group presentations to foster collaborative learning experiences. Furthermore, the study challenges traditional assessment methods, specifically highlighting term reports as the least effective option for stimulating students' interest in learning. The findings advocate for educators to reconsider assessment approaches, exploring alternatives aligned with students' preferences and engagement levels. While the new teaching formative assessment solution is well-received, addressing lower confidence in future career prospects signals the need for integrating practical elements into the curriculum and providing career counselling to boost students' confidence in their professional endeavours.
... For a better interpretation of the results and to better describe the potential expansion of energy crops in the region, the suitability maps were reclassified according to the FAO suitability classes: not suitable (N), marginally suitable (S3), moderately suitable (S2) and highly suitable (S1) (Figure 2c,d). The range of suitability values for each class was defined according to the method of [51] as follows: not suitable (N, S j ≤ 0.13), marginally suitable (S3, 0.14 ≤ S j ≤ 0.48), moderately suitable (S2, 0.48 < S j ≤ 0.80) and highly suitable (S1, S j > 0.80). ...
The current geopolitical and energy market instability calls for speeding up the EU clean energy transition to increase energy security in all the European regions and make Europe the first climate-neutral continent by 2050. Among renewable energies, modern bioenergy is a promising near-zero-emission fuel for increasing energy security in the heating, electricity and transport sectors while promoting growth and job creation, especially in rural areas. In such a context, energy crops will continue to play a key role. Since agricultural planning is a complex issue, especially when energy crops could compete with food ones, we propose an agroecological–economic land use suitability model (AE-landUSE model) to promote the sustainable use of land resources. The AE-landUSE model was developed by integrating cost–benefit analysis (CBA) and land use suitability analysis (LSA) within geographic information systems (GISs). Tested in the Basilicata region (Southern Italy), comparing two different energy crops (rapeseed and cardoon), the results show the model’s utility in identifying suitable areas for energy crops where the investments will be cost-effective. The proposed model will help decision-makers in energy-agricultural planning to increase energy security sustainably.
... According to Chen and Hwang (1992), the Weighted Sum Method is the simplest and best known method. This method was created by Fishburn (1967), where the determination of the global value of each alternative consists of the sum of the local value (referring to each criterion) multiplied by the weight of the respective criterion. ...
Public administration is responsible for managing public resources and offering various types of services to the population. Therefore, to ensure that the maintenance of state bodies is carried out in a responsible manner, both for the acquisition of goods and for the contracting of services, it is necessary to carry out bidding processes that follow constitutional principles. In this way, the use of Multi-Criteria Decision Analysis (MCDA) methods can help decision makers to solve selection problems in public institutions. In this context, the objective of this paper is to select, from a pre-defined list of ten alternatives, the three cars considered most suitable to meet the needs of an Own Social Security Regime Institute, allowing the opening of a bidding process more reliable. To carry out this selection, three MCDA methods were used to aid the choice: Analytical Hierarchical Process (AHP), PROMETHEE II and Weighted Sum Method (WSM). The results demonstrated that the three methods applied together managed to select the three best cars for carrying out the bidding process and that the use of these tools has great potential for the area of public management.
... The method's capacity to combine theoretical models into actual choice situations promotes well-informed, suitable, and efficient decision-making. Chen and Hwang [14] formulated the fuzzy TOPSIS method. Chu and Lin [15] developed a fuzzy TOPSIS technique for evaluating the selection process of robot selection. ...
The significance of t-intuitionistic fuzzy TOPSIS lies in its ability to address challenges related to uncertainty and ambiguity within the decision-making process. The incorporation of the "t" parameter as a t-norm and t-conorm operator offers a more comprehensive and precise approach, making it essential in scenarios where standard intuitionistic fuzzy TOPSIS approaches are insufficient. The implementation of this methodology across multiple domains enhances the dependability and robustness of decision-making procedures. The classification of the technique as an indispensable tool with a broad spectrum of applications is substantially bolstered by its fundamental qualities of versatility, adaptability, and flexibility. In this study, we introduce a novel distance measure called the lift-distance measure between t-intuitionistic fuzzy sets and examines its structural properties. Then, the superiority of this new distance measure is compared with some existing distance measures. To address circumstances with inherent ambiguity, we present a novel decision-making tool called the t-intuitionistic fuzzy TOPSIS technique based on the proposed distance measure. The integration of t-intuitionistic fuzzy terminology into this approach augments the versatility and inclusiveness of the TOPSIS methodology. The case analysis demonstrates that the developed strategy’s effectiveness and precision are superior to those of established alternatives. By providing a flexible and all-encompassing tool for decision-making in conditional environments, the application of this methodology possesses the capacity to generate significant favorable results. In addition, a comparative analysis is undertaken, which includes established TOPSIS methods, to demonstrate the improved performance of the proposed method. The comparison results demonstrate the ability of the proposed method to effectively capture the imprecision or vague differences in t-intuitionistic fuzzy sets so as to obtain more accurate and reliable ranking results.
... The TOPSIS method proposed by Hwang and Yoon can fully reflect the gaps between assessment objects and can be used to solve actual decision-making problems in different fields of application (Hwang & Yoon, 1981). The advantage of the TOPSIS method is that it can fully utilize attribute information sorting and does not require attributes to be independent (Chen et al., 1992). ...
The green supply chain of agricultural products (GSCAP) is a key link for rural revitalization and sustainable development in China. However, it faces various risks from internal and external environments that threaten its performance and stability. This paper proposes a novel framework and system for identifying and evaluating the main risks in the GSCAP from the perspective of agricultural enterprises. The framework combines social network analysis (SNA) and an improved technique for order preference by similarity to an ideal solution (TOPSIS) method. SNA is used to analyze the correlations and influences among different types of risks, while the improved TOPSIS method is used to rank the risks of different GSCAPs and identify the key risks in each supply chain. The framework and system are verified by a case study of CDYBIT, a leading platform of food safety big data service in China. The results show that the supermarket supply chain has the highest risk, followed by the group catering supply chain, and the five-star hotel supply chain has the lowest risk. The main risk factors for each supply chain are also discussed, and some suggestions for risk management are provided. This paper contributes to the literature by providing a comprehensive and systematic risk assessment framework and system for the GSCAP, which can help agricultural enterprises improve their risk awareness and response capabilities.
... Divergent viewpoints among decision-makers are the primary source of conflict in the decision-making process. [3,9] Almost all choice problems have many criteria, which are frequently in conflict. It's been a huge challenge to figure out how to solve such issues. ...
The method of generating intention with the scope of impact is called the decision making. It is the process which an unique or a group evaluates solutions and alternatives in order to found the most politic option while inspecting the problems or situations.Multi-attribute decision-making (MADM)MADM approaches are designed to discover the most satisfying of numerous comparison choices or to rank possibilities based on their connection to the analysed target. The strategies are utilized to identify the suitable alternative/solution when none of the evaluation parameters are the best.The Multi-attribute decision making theory offers a formal base for the establishment of a model, in which the key criteria is the individual parameters that result in an integrated assessment.MADMis a strategy for evaluating decisions with numerous co-attribute options in a complete and effective manner. The most appropriate options are ranked from most to least, and MADM methods are frequently used to get the best solution.In this paper, the decision-making algorithm is suggested and applied to purchase a new bike with the maximin method.
... The positive ideal solution maximizes the benefit criteria and minimizes the cost criteria, whereas the negative ideal solution maximizes the cost criteria and minimizes the benefit criteria. To apply this technique, the attribute values must be numerical, increasing or decreasing monotonously and have measurable units (Behzadian et al., 2012;Yon and Hwang, 1995;Chen and Hwang, 1992). The purpose of this method is to find the alternative closest to the positive ideal solution and the furthest from the negative ideal solution. ...
The COVID-19 pandemic has not only created public health issues but also sectoral problems and economic crises. As a response to this unexpected phenomenon, online communities have also started initiatives to tackle it. One of these initiatives was carried out in Turkey. Innovative project ideas were gathered from entrepreneurs and potential contributors regarding the problems brought about by the COVID-19 pandemic. The program occurred over three months (April 2020 to June 2020) through an open innovation platform in Turkey. The scope of this program is to collect business ideas from entrepreneurs and potential contributors, mature ideas with mentors and other entrepreneurs, and select the best ones by jury. In the process of evaluating the ideas, the weighted sum method (WSM) was used by the jury. The main purpose of this study is to reveal the effectiveness of the WSM via online communities in the idea evaluation phase. To demonstrate how this, we implemented different multi-criterion decision-making (MCDM) methods to the decision matrix dataset. We compare the results of WSM to those of the other two well-known (TOPSIS and VIKOR) MCDM methods. Besides, we conducted regression and sensitivity analysis to further clarify the differences between the results. Thereafter, we combine the rankings obtained from three MCDM methods by applying three aggregation methods as a compromise solution for the final decision. We find that the decision-makers can use WSM, TOPSIS, VIKOR, and aggregation methods separately according to the criterion weighting and the level of confidence in the scoring of the alternatives.
... Additionally, it is favored for streamlining processes and reducing uncertainty and vagueness in the chosen criteria [62,63]. Hwang and Yoon developed TOPSIS as a multiple criteria decision-making (MCDM) technique in 1981 [70]. Later, Chen and Hwang [71] introduced and integrated the fuzzy technique. ...
This research focuses on elucidating the attributes of a Sustainable Healthcare Supply Chain (SHSC) that play a pivotal role in enhancing patient safety, particularly in developing nations. Patient safety in healthcare supply chains is paramount, particularly in the face of inherent risks and vulnerabilities associated with disruptions and uncertainties. A hybrid selection model, integrating factor analysis, structural equation modeling (SEM), and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is introduced to rank these attributes. Twenty-two SHSC attributes are categorized into four facets: social, environmental, economic, and technological. A survey conducted across five Cambodian provinces gathered 361 valid responses from healthcare professionals, forming the basis for a structural SHSC model. This model is subsequently implemented in a Phnom Penh tertiary hospital. The findings underscore the imperative of incorporating patient safety considerations into healthcare supply chains. The hybrid selection model helps healthcare leaders figure out what factors are most important for patient safety and rank them. This gives them information they need to come up with effective strategies and long-lasting projects. The study's outcomes provide actionable insights for healthcare stakeholders. The multi-analytical approach of the model offers a comprehensive perspective to address supply chain challenges, reduce extraneous costs, and minimize environmental footprints. In essence, the effective implementation of sustainable healthcare supply chain strategies not only enhances care quality and fortifies patient safety but also aligns with the broader objectives of healthcare entities.
... [22] Later, this method was used in various research areas. It was even described as one of the most promising multi-attribute decision analysis, for structuring complex decision-making issues [23]. Great interest in the method and new applications influence some changes, extensions, and improvements. ...
The article presents research on factors that influence the safety of tram passengers at the tram stop. The authors, based on the literature review, analyse the causes of adversity events. Based on them, the authors selected factors influencing passenger safety at tram stops. The selected factors were analysed with the DEMATEL (Decision Making Trial and Evaluation Laboratory) method. Analysis allows one to find and analyse cause-and-effect relationships between factors. The factors under investigation were: (1) passenger behaviour, (2) behaviour of other road users, (3) equipment standards and parameters of stops, (4) type of stop, including: separation from other traffic zones, (5) mutual visibility of traffic participants, (6) number of passengers and volume of passenger exchange, (7) atmospheric conditions, including daylight, (8) the presence of service points.
... The TOPSIS method was created by Hwang and Yoon (1981) and later outlined by Chen and Hwang (1992). The basic principle of TOPSIS is that the chosen alternative should have the shortest distance from the ideal solution and the farthest distance from the perfect negative solution. ...
... The TOPSIS method was created by Hwang and Yoon (1981) and later outlined by Chen and Hwang (1992). The basic principle of TOPSIS is that the chosen alternative should have the shortest distance from the ideal solution and the farthest distance from the perfect negative solution. ...
... Based on a large number of drawdown operation rules, multi-criteria decision-making (MCDM) analysis provides an efficient method for identifying the best scheme from all alternatives, which can greatly improve the synergetic benefits of multipurposes for the reservoir. Since the 1960s, MCDM analysis has been used to assess reservoir drawdown operation schemes [19][20][21]. Keshavarz et al. [22] proposed a new combined distance-based assessment (CODAS) method using Euclidean distance as the primary metric and Taxicab distance as the secondary metric to select the farthest alternative as the best solution. It is very interesting to explore the CODAS method for identifying the best reservoir operation rule since the method has an effective and stable result according to the sensitivity analysis as well as is widely used to deal with MCDM problems [23,24]. ...
The seasonal operation of drought-limited water level (DLWL) can efficiently boost the synergies of hydropower production and drought defense. For the first time, this study proposes a seasonal DLWL operation framework for mimicking reservoir drawdown operation to improve hydropower output and mitigate drought risk. Firstly, three statistical analysis methods were used to divide the drought season into three segments. And then, the simulation model of seasonal DLWL operation was configured to evaluate the effect of reservoir drawdown operation on risk and benefits. Lastly, the combined distance-based assessment method was employed to identify the best scheme of seasonal DLWL operation. The Three Gorges Reservoir sited in the Yangtze River of China constitutes the case study. The results suggested that the proposed framework could facilitate reservoir drawdown operation to achieve 2346.95 million kW·h (7.0% improvement) in hydroelectricity production and 3.3% in utilization efficiency of water resources, while could reduce 7.4% in drought risk. This study not only can provide scientific and technical support for reservoir drawdown operation benefiting synergies of hydropower generation and drought defense but also can suggest policymakers with various favorable strategies to experience potential risks and benefits of seasonal DLWL operation in the interest of sustainable hydropower development.
The challenges resulting from rapid economic growth, urbanization, and increased motorization in developing nations necessitate a comprehensive and sustainable approach to urban public transport planning. While sustainable urban public transport (SUPT) planning offers a solution, the complexity of choosing suitable policy measure options remains a challenge. This study first introduces a decision support framework (DSF) that integrates the sustainable urban public transport manual (SUPTM) adopted for generating the potential SUPT policy measure options, the KonSULT knowledge base applied for providing the performance scores of each measure option for all determined criteria, and the HMADM (including FAHP, FSM, and TOPSIS) technique to create, rank, and select SUPT policy measure options tailored to medium-sized urban areas in developing nations. A case study of Khon Kaen City, Thailand, illustrates the practical application of the framework, resulting in a set of 31 (91.2%) out of the total of 34 ranked policy measure options. Comparing these prioritizations with the city’s existing plan reveals a substantial agreement, which suggests the potential applicability of the DSF. Overall, the DSF marks a significant advancement in SUPT planning, which is crucial for shaping efficient, equitable, and environmentally conscious urban mobility in developing countries, which are undergoing transformative change.
İklim değişikliği, biyoçeşitlilik ve toprağın iyi yönetilmesi dünyadaki hızlı nüfus artışı ile birlikte kıt olan bu tür kaynakların daha iyi yönetilmesi ve verimli kullanılması gerekliliğinin önemini artırmaktadır. Tıbbı ve aromatik bitkiler de (TAB) bu kaynaklar arasında yer almakta ve ekonomik açıdan da bir katma değer potansiyeli bulunmaktadır. Doğadan doğrudan veya kültür yolu ile üretimi gerçekleştirilen TAB’ların işlenmesi için tesis yeri seçimi önemli bir stratejik karar unsuru olmaktadır ve genel olarak tesis yeri seçimi problemi, işletmelerin veya örgütlerin karşılaştığı en temel stratejik karar verme problemlerinden biri olarak ortaya çıkmaktadır. Çok fazla faktörün minör veya majör etkilerinin bulunduğu bu karmaşık karar verme sürecini çözümlemek için bu çalışmada çok kriterli karar verme yöntemlerinden (ÇKKV) biri olan EDAS (The evaluation based on distance from average solution) metodolojisinin adımları izlenmiştir. Bunun yanı sıra bulanık teorinin belirsizlik ve eksik bilgi ile baş edebilme yeteneğinden faydalanarak (trapezoidal fuzzy numbers – yamuk bulanık sayılar) problemin çözümüne ulaşmada zaman ve kaynak tasarrufu olarak önemli bir avantaj elde edilmiştir. Çözüm sürecinde üç karar verici ve altı alternatif lokasyonu dilsel terimlerle değerlendirerek bir öncelik sıralaması oluşturulmuş ve en uygun konum (A2- Seyitler Yerleşkesi) belirlenmiştir.
Public transportation is a great challenge Brazilian cities are facing nowadays. The accelerated growth of cities boosts the demand for transport, which generates an increase in the number of vehicles on urban roads, as well as the need for improvement of road infrastructure. Public transport services should play an important role in promoting good transport for users, being more attractive and generating greater efficiency in the use of urban space. This study is aimed to develop a multicriteria evaluation model for public transport services. Using this method it was possible to structure an evaluation model which displays the perception of users on evaluation aspects. After the structuring of the model, a field survey was carried out to evaluate part of the Integrated Transportation System (SIT) of Florianópolis. The evaluation model developed can help the management of public transport services, supporting the decisions of public managers and administrators.
No decision can be made without first taking the decision-making process into consideration. Multi-criteria decision-making (MCDM) seeks to identify the optimal option by taking into account multiple criteria during the selection process. Numerous tools and techniques from MCDM can be used in a variety of sectors, including engineering design and finance. Recently, because of the generalization ability and more flexibility of Q-rung orthopair fuzzy sets (Q-ROFS), it has been used widely to solve MCDM problems. However, under uncertainty, evaluating an alternative in the form of Q-ROFS with a full reliability is not always possible. Therefore, in this paper, we have defined the notion of Q-rung orthopair Z-numbers, in which the reliabilities of an evaluated Q-ROFS have also been considered to make decision-making more comprehensive regarding the uncertainty. Mathematically, a Q-rung orthopair Z-number \(Z_Q=(C_Q, ~R_Q)\) defined on a non-empty finite set X is a pair of two Q-ROFS, where \(C_Q\) is Q-ROFS defined on X and \(R_Q\) is the reliability of the \(C_Q\) in the form of Q-ROFS. Further, arithmetic operations on these Z-numbers have been introduced. Moreover, a series of dice similarity measures have been defined for Q-rung orthopair Z-numbers. To solve the MCDM problems, a TOPSIS method based on these distance measures has also been discussed. Further, an application of the proposed method has been studied to solve an industrial problem. Furthermore, a sensitivity analysis of the involved parameters has been done to illustrate the stability and efficiency of the proposed approach. Finally, a case study has been conducted investigating the allocation of healthcare resources, along with a comparative analysis of the outcomes attained using the proposed technique. This analysis intends to demonstrate the proposed method’s validity and superiority. Further, it has been shown by numerical experiments that decision-making with Q-ROZN is more suitable since it gives the decision-maker additional freedom in terms of the reliabilities of evaluated Q-ROFS.
This study quantified uncertainties involved in assessing the future flood vulnerability in 33 urban areas with population exceeding designated thresholds in South Korea. The driver-pressure-state-impact-response (DPSIR) framework was utilized as the study procedure, integrating social, economic, and environmental factors. In addition, a total of 220 cases of combinations were examined, encompassing twenty general circulation models combined with shared socioeconomic pathway scenarios, five weight determination methods, and three multi-criteria decision-making (MCDM) techniques, as sources of inherent uncertainties in the process. The rankings of urban flood vulnerability (UFV) for the selected cities were comprehensively assessed considering all combinations, followed by an analysis of variance test to investigate contributing sources of uncertainties. As a result, Incheon and Busan were found to be vulnerable to flooding, while Yeongcheon and Andong appeared to be safe cities. Some cities exhibited wide ranges in their rankings, such as Daegu, Yangpyeon, and Jeongeup. The identified contributing sources were weighting (58%), MCDM (27%), and the combination of weighting and MCDM methods together (15%). This study revealed that weight determination methods and MCDM techniques are the primary sources of uncertainties in the assessment of future UFV instead of multiple GCMs and SSPs. This finding underscores the importance for decision-makers and stakeholders to carefully consider these uncertainties for sustainable flood risk management and prevention.
Triangular fuzzy numbers (TFNs) are widely used for selection problems to determine expert opinions using linguistic expressions. Some aggregation procedures are developed to determine expert opinions more accurately. However, there is a need for a simple and more useful procedure to solve the selection problems more suitably. For this purpose, our study offers a triangular, exparabolic, and parabolic area calculation-based approximation approach for TFNs to aggregate the possible hedges (very and more or less) for TFNs. Hence, this aggregation procedure provides a tuning opportunity for classical TFN expressions to capture possible tuning processes to reflect the hesitancies of experts. The technique for order preferences by similarity to ideal solution (TOPSIS) method is applied in the two studies from extant literature, and suitable alternatives are determined as a result of the ranking process. Finally, a comparative analysis is presented to illustrate the efficiency of the proposed procedure. The conventional TOPSIS model’s ranking scores are very close for exemplified examples (i.e., 0.5308, 0.4510, 0.4550 and 0.5304, 0.4626, 0.4940), but the proposed model’s result has fluctuated for the same examples (i.e., 0.346, 0,669, 0,567 and 0.208, 0.991, 0.148). So, the main advantage of the proposed aggregation procedure is the alternative ranking scores separation capability analyzed with their linguistic diversification.
In the exploration of human-machine collaborative scoring of subjective assignment (HMCSSA) problems, it is crucial to note that the workloads assigned to humans and machines are determined by thresholds at various levels of granularity within the human-machine task allocation model. To address this issue, a three-phase framework for optimization and decision making in HMCSSA problems is constructed by combining multi-objective evolutionary algorithms (MOEAs) with multi-attribute decision making method. Specifically, we present a bi-objective threshold optimization model to achieve a trade-off between human costs and scoring fairness in HMCSSA problems. Moreover, four well-known MOEAs are employed for solving the optimization model to search the Pareto optimal thresholds. Meanwhile, the technique for order of preference by similarity to ideal solution (TOPSIS) method is utilized to determine the best human-machine task allocation schemes based on the preferences of decision makers. The numerical experiments are conducted on eight prompts of the ASAP data set to validate the effectiveness and superiority of the proposed framework. In particular, the best task allocation scheme attains the fairness gain of 53.76% with the human participation rate of 21.77% on average.
Abstracts
This research work covers three highly dominating reverse degree-based topological descriptors evaluated for the three-dimensional hexagonal close-packed (HCP) crystal structure lattice. HCP crystal lattice has a highly symmetrical and elegant crystal structure, and we have observed that results obtained from symmetrical structures draw symmetry in the numerical formulation obtained from topological descriptors. For this purpose, we will investigate whether the HCP lattice formed by an odd pair of unit cells is the best or an even pair of unit cells forming the lattice and how they behave in a dominating sense when investigated through the conclusions obtained from QSPR modeling. The QSPR model has been proposed to check the efficiency of each specified topological descriptor for five highly commendable physio-chemical properties: melting or boiling point, density, molar heat capacity, and enthalpy. Further, we have discovered the ideology to obtain the best possible structure when investigated and established on a statistically and mathematically strong proving and to what extent we can extract from QSPR to implement MCDM techniques, here considering TOPSIS that provide the best HCP structure lattice rankings. The obtained results may be helpful for researchers to better understand the structure and studying different physical/chemical properties of HCP crystal lattice.
In many developed economies, the diesel engine is very important for transportation and farming. There is a lot of research being done in the field of renewable energy to replace conventional energy sources because of the major environmental issues and the rising expense of diesel. Diesel engine cannot be reinstate because of its efficient performance at higher power and reliability with alternative engines. Diesel engine emissions are very harmful to the atmosphere and human health. The main contaminants in diesel engines are smoke and NOx, which need to be effectively monitored. A numerous research is going on to diminish the emissions from CI engines by using some additives as well as the use of alternative fuels. This experimental inquiry was conducted to identify a suitable addition to lower exhaust emissions and improve CI engine performance. The trials used various mix ratios of pure diesel and blends of diesel and diethyl ether-2-methoxy ethyl ether. Mixing of 5% DEE and 5% MXEE with 90% diesel on volume basis (D90–DEE5–MXEE5) showed optimum results of emission and performance. Low exhaust emissions (HC 63.15%, CO 60.00%, and Smoke 18.29%) found to be substantial at peak loads and performance increase (decreasing in BSFC 5.00% and increasing in BTE 3.00%) were compared to mixture D90-DEE5-MXEE5 with diesel (at standard engine conditions). However, NOx rises (2.60%).
Calibrating microscopic car-following (CF) models is crucial in traffic flow theory as it allows for accurate reproduction and investigation of traffic behavior and phenomena. Typically, the calibration procedure is a complicated, non-convex optimization issue. When the traffic state is in equilibrium, the macroscopic flow model can be derived analytically from the corresponding CF model. In contrast to the microscopic CF model, calibrated based on trajectory data, the macroscopic representation of the fundamental diagram (FD) primarily adopts loop detector data for calibration. The different calibration approaches at the macro- and microscopic levels may lead to misaligned parameters with identical practical meanings in both macro- and micro-traffic models. This inconsistency arises from the difference between the parameter calibration processes used in macro- and microscopic traffic flow models. Hence, this study proposes an integrated multiresolution traffic flow modeling framework using the same trajectory data for parameter calibration based on the self-consistency concept. This framework incorporates multiple objective functions in the macro- and micro-dimensions. To expeditiously execute the proposed framework, an improved metaheuristic multi-objective optimization algorithm is presented that employs multiple enhancement strategies. Additionally, a deep learning technique based on attention mechanisms was used to extract stationary-state traffic data for the macroscopic calibration process, instead of directly using the entire aggregated data. We conducted experiments using real-world and synthetic trajectory data to validate our self-consistent calibration framework.
This paper focuses on a comparative analysis between two multi-criteria decision-making (MCDM) methods, called the Simple Ranking Process (SRP) and Faire Un Choix Adéquat (FUCA). Two examples are used to reveal the similarities and differences between these two methods. The findings established that both methods share the use of an internal ranking system as a fundamental procedure. However, beyond this commonality, significant differences distinguish these methods from each other. These differences include variations in the number of steps within their algorithms, distinct approaches used in executing the internal ranking system, discrepancies in the alternative scores, different behavior when dealing with complex decision-making problems, and differences in the generated rankings.
Bu çalışma kapsamında Bitlis yöresi ignimbiritlerinden olan pomza taşı, Ahlat taşı ve Güroymak taşlarının toz haline getirilmesiyle elde edilen harç numunelerinin dayanım sonuçları bulanık mantık yöntemiyle incelenmiştir. %10, %20 ve %40 oranında taş tozunun çimentoyla ikame edilmesiyle oluşturulan numunelere sırasıyla ultrasonik ses geçirgenlik, eğilmede çekme ve basınç dayanımı deneyleri uygulanmıştır. Elde edilen sonuçlar kullanılarak her bir deney için birer bulanık mantık modeli oluşturulmuştur. Bu model ile deney sonuçlarının karşılaştırılmasıyla; yüzdesel olarak ortalama hata, ortalama mutlak hata, en büyük mutlak hata ve korelasyon katsayısı elde edilmiştir. Sonuç olarak deneysel sonuçlar ile bulanık model sonuçları arasında %99 oranında benzerlik oranı elde edilmiştir. Bu durum bulanık mantık yönteminin inşaat mühendisliği laboratuvar deneyleri için kullanılabilir bir yöntem olduğunu ortaya koymuştur.
We have proposed a data-driven method for spatio-temporal analysis of car crashes based on the Multi Criteria Decision Making (MCDM) procedure in the Zanjan city, NW Iran which are recorded in the period 2019-2020. A combination of Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used in this paper to accurately identify the spatio-temporal interactions exist in car crashes. A data-driven AHP-TOPSIS procedure is arranged based on assigning proper weights to the time series related to the peak of accidents. On the other hand, for spatial analysis, the Kernel Density Estimation method was used to create the continuous-value maps of different traffic accidents and then classified using Natural Breaks Classifier. In fact, the proposed methodology can be used to identify car crash hotspots by considering spatio-temporal interactions as well as addressing exaggerated weightings arising from knowledge-driven modeling. By using the spatio-temporal interaction maps in which the location and time of crashes are considered, simultaneously, it is possible to provide a new scientific strategy for identifying car crash hotspots which can lead to better traffic management, improved allocation of resources, and enhanced prevention regulations.
In this study, hydrothermal synthesis was employed to produce Fe3O4 nanoparticles for the methylene blue removal from an aqueous medium. The production of magnetite nanoparticles involved the utilization of Fe2+ and Fe3+ salts, and their respective solutions were created at pH levels of 10, 11, and 12, subsequently subjected to autoclave treatment. The evaluation of pH-induced variations in nanoparticle characteristics was conducted through X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Field emission scanning electron microscopy (FESEM), vibrating-sample magnetometer (VSM), and Dynamic light scattering (DLS) analyses. pH levels within the synthetic medium yielded diminutive Fe3O4 nanoparticles characterized by augmented saturation magnetization, heightened zeta potential, and a narrower size distribution. Following nanoparticle synthesis under varied pH conditions, their efficacy in methylene blue (MB) adsorption was investigated. Notably, nanoparticles synthesized at pH 11 demonstrated the highest adsorption capacity, registering maximum MB adsorption capacities of 188.68 mg/g, while pH 10 and 12 counterparts exhibited capacities of 169.49 mg/g and 175.44 mg/g, respectively. The adsorption processes conformed to the Langmuir–Freundlich isotherm model, with the pseudo-second-order model offering superior fitting to elucidate MB adsorption kinetics, thereby indicating the involvement of chemical adsorption mechanisms. It was discerned that MB adsorption encompassed both physical and chemical mechanisms, encompassing electrostatic attraction between the negatively charged surface of the nanoparticles and the cationic dye, as well as electron exchange interactions between MB and the functional groups present on the adsorbent surface. Thermodynamically speaking, this adsorption process exhibited an exothermic nature, with a preference for ambient temperatures. Magnetic separation post-adsorption was conveniently executed, and all nanoparticles demonstrated potential for reuse for a minimum of five cycles. Moreover, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method was employed to assess and select the most favorable alternative from the available options. Based on the evaluation of 27 distinct criteria, it was determined that Fe3O4 synthesized in an environment with pH 11 emerged as the optimal choice, aligning with the initial findings from the adsorption assessments.
Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded on the weight optimization principle. Firstly, the notion of a probabilistic hesitant fuzzy set is expanded to a (p,q)-rung. Secondly, the determination of subjective and objective weights is accomplished through the utilization of the Analytic Network Process (ANP) and the Entropy Method. According to the degree of deviation and dispersion of each weight, an optimal objective function is constructed, and the neural network is used to iteratively solve for the best scheme of the comprehensive weight. Subsequently, the Elimination Et Choice Translating Reality (ELECTRE) approach was refined and applied to decision-making in the (p,q)-rung probabilistic hesitant orthopair fuzzy environment. Finally, comparative analysis was used to demonstrate the new method’s effectiveness and superiority.
In order to find a reasonable and effective approach to describe the information contained in a specific Z-number, we introduce information entropy into Z-number environment in this paper, and investigate its applications in multi-attribute decision-making (MADM) issues. Moreover, aiming at the problem with the weighting indicated by Z-number values, we propose two novel weighting methodologies based on conditional entropy and sigmoid function, respectively. Firstly, on the basis of the maximum entropy principle, the optimization model to calculate the underlying probability distribution of Z-number is introduced. And then, we define Z-number pseudo-information entropy, and a novel Z-VIKOR method is proposed to solve a selecting regional circular economy development plan issue from the perspective of information entropy. Furthermore, we propose Z-number pseudo-conditional entropy, and the relationship between Z-number pseudo-information entropy and Z-number pseudo-conditional entropy is investigated. Subsequently, a weighting method based on information entropy of Z-number is proposed. In addition, we also introduce the weighting approach based on the sigmoid function decision-making method. Finally, we introduce a government new energy investment problem to verify and compare the effectiveness of the new weighting approaches. The new method gives a solution to the problem related to Z-number from the perspective of information entropy.
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