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Sustainable design of infrastructures has become a major matter of study since the recent establishment of the Agenda 2030. This paper provides a systematic literature review on the use of multi-criteria decision making techniques used so far for the sustainable design of bridges. Special attention is put as well on how the reviewed studies assess the sustainable performance of bridge designs along their life cycle from the economic, the environmental and the social perspective. Although SAW and AHP are recurrently used in the sustainable assessment of bridges, the analysis of the most recent articles show that the application of TOPSIS and PROMETHEE techniques are gaining increasing relevance for such purpose. Most of the studies focus on the research of the construction and the maintenance stage of bridges. However, a need for further analysis is identified when it comes to the assessment of the impacts resulting from the End of Life cycle stage of bridges from a sustainable point of view. The use of intuitionistic and neutrosophic logic have been detected as emerging alternatives to the fuzzy approach of decision making problems. [ABSTRACT FROM AUTHOR]

In existence of interval-valued parameters and managerial limitations, multicriteria decision-making (MCDM) problems become more complex than their original situation. In such complex cases, the classical MCDM solution methods mainly cannot handle the managerial constraints of the problem and, therefore, become useless. This paper focuses on an MCDM problem such as establishment of the branches of a glass production company in all districts (provinces) of Iran in existence of interval-valued parameters and some managerial limitations like total available budget, number of selected branches for establishment, etc. To overcome the aforementioned difficulties, a novel modified version of the simple additive weighting method, which is of the well-known MCDM approaches of the literature, is formulated as a mixed integer linear formulation. The novelty of this formulation can be summarized by the following points: 1) to cope with the interval values of the criteria; 2) to keep the possibility of selecting a set of best locations among all possible locations; and 3) to handle the managerial limitations of the problem. The proposed formulation is validated by the real data of the case study, and its sensitivity is studied in detail. Finally, the performance of the proposed approach is compared to an alternative proposed solution approach. [ABSTRACT FROM AUTHOR]

Copyright of TEME: Casopis za Društvene Nauke is the property of TEME: Casopis za Drustvene Nauke and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The evaluation of cultural websites is a complicated procedure that depends on several criteria. The main contribution of this paper is on showing how this process may be implemented. For this reason, different multi-criteria decision-making methods are combined and compared for processing the results of the evaluation. More specifically, the paper provides the criteria for evaluating a website of cultural heritage and presents the application of Analytical Hierarchy Process for estimating the weights of the criteria. Then, it compares two different multi-criteria decision-making models, fuzzy simple additive weighting and fuzzy weighted product model, for being combined with Analytical Hierarchy Process and processing the results of the evaluation. The evaluation involves 29 websites of the conservation labs of the international museums and useful conclusions are extracted about the application of all methods and the combination of Analytical Hierarchy Process with fuzzy simple additive weighting and fuzzy weighted product model. [ABSTRACT FROM AUTHOR]

Copyright of SDU Journal of Engineering Sciences & Design / Mühendislik Bilimleri ve Tasarım Dergisi is the property of Journal of Engineering Sciences & Design and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Military Technical Courier / Vojnotehnicki Glasnik is the property of Military Technical Courier / Vojnotehnicki Glasnik and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

An introduction is presented in which the editor discusses various reports within the issue on topics including decision support approach, multiple criteria decision making, and aggregation operators.

This paper proposes a WiFi offloading algorithm based on Q-learning and MADM (multiattribute decision making) in heterogeneous networks for a mobile user scenario where cellular networks and WiFi networks coexist. The Markov model is used to describe the changes of the network environment. Four attributes including user throughput, terminal power consumption, user cost, and communication delay are considered to define the user satisfaction function reflecting QoS (Quality of Service), and Q-learning is used to optimize it. Through AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) in MADM, the intrinsic connection between each attribute and the reward function is obtained. The user uses Q-learning to make offloading decisions based on current network conditions and their own offloading history, ultimately maximizing their satisfaction. The simulation results show that the user satisfaction of the proposed algorithm is better than the traditional WiFi offloading algorithm. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses various reports within the issue on topics including evaluation of multi-criteria decision making methods, genetic-fuzzy mining method, and the diminishing utility decision model (DUDM).

As a country with the largest sea area in Asia, Indonesia will certainly encounter the threats to the maritime aspect. The aim of this paper is to make an analysis of national maritime security of concerning the regional development effect. This paper uses a SWOT approach (Strengths, Weaknesses, Opportunities, and Threats), Fuzzy Multi-criteria Decision Making (FMCDM), and Borda method. SWOT analysis is used to identify internal and external factors in national maritime security, and strategic determination. Fuzzy MCDM (FMCDM) method is used to select the right strategy in maritime security control. The Borda method is used to define the sub-strategy, priorities of the selected strategy. The result of this paper with SWOT analysis is to identify four strategies, likely Strategy 1 (SO); Strategy 2 (WO); strategy 3 (WT); Strategy 4 (ST). Based on FMCDM method, Strategy 1 (SO) has a weight of 0.256 as a third rank; Strategy 2 (WO) has a weight of 0.26 as a second rank; Strategy 3 (WT) has a weight of 0.208 as a fourth rank; Strategy 4 (ST) has a weight of 0.276 as a first rank. Then, the strategy chosen is Strategy 4 (ST). Based on Borda method, the first priority of sub-strategy from strategy 4 (ST) is to increase the percentage of State Budget for the maritime sector in the development of Navy Capability and other stakeholder to carry out the operation of sea crime action with allocation of 22,587%. [ABSTRACT FROM AUTHOR]

In this paper, we propose an evolutionary multiobjective regenerator placement strategy for elastic optical networks (eMORP). The proposed optimization strategy uses the genetic algorithm NSGA-II to determine non-dominated solutions when the call request blocking probability and the total amount of regenerators used in the network are taken into account. In our simulations, we considered the amplified spontaneous emission noise generated by optical amplifiers (in-line, booster, and pre-amplifier) as physical impairment. Two recently proposed heuristics for regenerator assignment have been used, together with the regenerator placement strategies proposed and analyzed in this paper, for comparison purpose. The results obtained for two different network physical topologies state the efficiency of eMORP. Our regenerator placement strategy reduced considerably the call request blocking probability for the same number of regenerators in the network, as well as it acquired efficient solutions with just a fraction of the nodes with regeneration capability in comparison to other heuristics presented in the literature. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Central European Agriculture is the property of Journal of Central European Agriculture and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Operational research is a scientific discipline related to the decision theory that allows determining solutions for specific problems related to, for example, widely understood transport. Increasingly popular in this field are issues related to the domain of the green urban transport. In order to support the decision-making process in this area, methods of multi-criteria decision analysis (MCDA) are used more and more often. However, if we solve a specific problem using different MCDA methods, we get different rankings, as each method has a different methodological basis. Therefore, the challenge is how to make a reliable decision. This paper presents a numerical example from the green urban transport domain, which is solved by six different MCDA methods that return a complete ranking. We measure the similarity of these rankings using coefficients rw and WS, and then we propose a simple way of determining a compromise solution. The obtained compromise ranking is guaranteed to be the best match to the selected MCDA methods' rankings, which is proved in the paper. Finally, possible directions for further development work are identified. [ABSTRACT FROM AUTHOR]

A single-valued neutrosophic multi-set is characterized by a sequence of truth membership degrees, a sequence of indeterminacy membership degrees and a sequence of falsity membership degrees. Nature of a single-valued neutrosophic multi-set allows us to consider multiple information in the truth, indeterminacy and falsity memberships which is pretty useful in multi-criteria group decision making. In this paper, we consider sequences of intuitionistic fuzzy values instead of numbers to define the concept of intuitionistic fuzzy-valued neutrosophic multi-set. In this manner, such a set gives more powerful information. We also present some set theoretic operations and a partial order for intuitionistic fuzzy-valued neutrosophic sets and provide some algebraic operations between intuitionistic fuzzy-valued neutrosophic values. Then, we develop two types of weighted aggregation operators with the help of intuitionistic fuzzy t-norms and t-conorms. By considering some well-known additive generators of ordinary t-norms, we give the Algebraic weighted arithmetic and geometric aggregation operators and the Einstein weighted arithmetic and geometric aggregation operators that are the particular cases of the weighted aggregation operators defined via general t-norms and t-conorms. We also define a simplified neutrosophic valued similarity measure and we use a score function for simplified neutrosophic values to rank similarities of intuitionistic fuzzy-valued neutrosophic multi-values. Finally, we give an algorithm to solve classification problems using intuitionistic fuzzy-valued neutrosophic multi-values and proposed aggregation operators and we apply the theoretical part of the paper to a real classification problem. [ABSTRACT FROM AUTHOR]

According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision Making (MCDM) models in solving decision-making problems in different industry sectors such as supplier selection or investment assessment. Many different MCDM models have been introduced over the years, and each model is uniquely dedicated into solving a particular problem. There is very little MCDM models incorporated with fuzzy set theory to support decision makers with decision-making problem in uncertain environments. This paper introduces a Fuzzy MCDM-based approach to the problem by utilizing Fuzzy-Analytic Hierarchical Process (FAHP) and Weighted Aggregated Sum Product Assessment (WASPAS) methods to support the decision makers. The aim of the paper is developing a decision-making tool that supports the decision maker in deciding the suitable supplier in garment industry under fuzzy environment. The proposed MCDM model is applied to a real-world case study to demonstrate the application steps of the model as well as its feasibility. The model assisted in successfully its proposed goals that resulted in an optimal supplier in garment industry. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to measure the supply chain competitiveness of the e-commerce industry in Indonesia. Design/methodology/approach: The study used a multi-criteria decision-making model based on the analytic hierarchy process. Four main criteria are used to measure the supply chain competitiveness, i.e. cost, differentiation, sustainability and infrastructure. Findings: The findings of this study show that cost is the most important criterion with a degree of importance of 33.19%, followed by infrastructure of 29.40%, differentiation of 27.96% and sustainability of 9.45%. It shows that the internally controlled strategy contributes about 70% of supply chain competitiveness. The internal infrastructure criterion that consists of software and hardware contributes 65.92% to the whole infrastructure criterion. The internal infrastructure then contributes 19.38% to supply chain competitiveness. Therefore, the internally controlled strategies and internal infrastructure contribute up to 90.08% to the supply chain competitiveness of e-commerce in Indonesia. This result implies that to attain the supply chain competitiveness, the company must carry out strategies focusing on the performance such as cost, differentiation, sustainability as well as on the internal infrastructure such as software and hardware. Research limitations/implications: In this paper, the authors limited their study to the business to business (B2B) and business to consumer (B2C) players because these two platforms have been experiencing a very rapid growth. While e-commerce business can take many platforms besides B2B and B2C, the future research should include other platform such as consumer to consumer as well. Because the focus in this study is more the information and material flows, it will be of great interest if the future research covers the platform of mobile payment as well that guarantee the ease of cashflows within supply chains. Also, with the occurrence of the Covid-19 pandemic when this paper was written, in the near future, it is then of great interest to incorporate the pandemic context into the proposed model used in this study. The further study should analyze long-term changes happened as the result of pandemic such as behavioral changes of online shopping from customer side or shift in e-commerce supply chain infrastructure and inventory practice. Practical implications: With this study, it is expected that it can be determined which criteria contribute the most to the supply chain competitiveness of the e-commerce industry in Indonesia that will be useful for industry player. Originality/value: E-commerce development in Indonesia is still facing serious challenges. The multi-criteria decision making approach used in this research lays a foundation of how supply chain competitiveness is determined based on the judgment of experts coming from major companies within the supply chain. [ABSTRACT FROM AUTHOR]

This paper introduces and further applies an approach to support the decision makers in construction projects differentiating among a variety of deep excavation supporting systems (DESSs). These kinds of problems include dealing with uncertainty in data, multi-criteria affecting the decision, and multi-alternatives to select one from them. The proposed approach combines the analytic hierarchy process (AHP) with the fuzzy technique for order of preference by similarity to ideal solution (fuzzy TOPSIS) in a multicriteria decision-making (MCDM) model. The MCDM model emphasize the ability to combine expert knowledge, cost calculations, and laboratory test results for soil properties to achieve the scope. The model proved it had a superior ability to deal with the complexity and vague data that are related to construction projects. Furthermore, it was applied to a real case study for a governmental housing project in Egypt. Secant pile walls, sheet pile walls, and soldier piles and lagging are selected and studied as being the most common DESSs and as they satisfy the project requirements. The model utilized four criteria and fourteen comparing factors, including site characteristics, safety, cost, and environmental impacts. Based on the results of the model application on the investigated case study, a decision was reached that using secant piles as a supporting system in this project is mostly preferred. Furthermore, sheet pile wall, and soldier piles and lagging, come next in the ranking order. A sensitivity analysis is carried out to investigate how sensitive the results are to the criteria weights. In addition, the paper discusses in detail the reasons and factors which affect and control the decision-making process. [ABSTRACT FROM AUTHOR]

With the continuous improvement in user demand and the increasingly obvious complexity characteristics, such as strong coupling and nonlinearity of the system, it has become a new problem faced by the decision making of conceptual design. Decision-making methods in conceptual design such as traditional information axioms and the multi-criteria decision-making (MCDM) framework cannot provide a good solution for systems with strong coupling and nonlinearity. To fill these gaps, this paper proposes a decision-making method of design for a coupling system based on a complexity composite method (DMDCC). DMDCC is composed of a prediction model and a synthetic paradigm. In the early stages of decision making of design, design-centric complexity (DCC) theory is used to preliminarily sort the schemes. Then, driven by the twin data of existing products, the complexity of function units is obtained by using the prediction model. The complexity of different function units is composited by the composite paradigm to obtain the total function realization probability of the design scheme. A more accurate calculation of the total function realization probability of new products can assist designers to judge the scheme from the perspective of function and help to guide the decision making of the design of new systems' development scientifically and reasonably. The engineering example of the bulk traditional Chinese medicine dispensing device is used to verify the scientific effectiveness of the research. [ABSTRACT FROM AUTHOR]

Life cycle sustainability assessment (LCSA) is an assessment method capable of supporting decision makers toward a more sustainable system. In this paper, a systematic literature review regarding LCSA application in the energy field was performed. The main challenges, methodological approaches, and sustainability indicators used to perform LCSA studies in this sector were highlighted. Peer-reviewed articles published until December 2020 were considered. The research portfolio consisted of 34 publications. According to the results, the energy sector functions as a platform for LCSA application and methodological development, as the number of studies applying this methodology in energy-related systems grew exponentially over the years. The review suggests that the choice of the life cycle concepts (system boundary, impact categories, etc.) is a critical point, as basically, every study presented different characteristics of life cycle studies. An even bigger diversity regarding sustainability indicators was found, especially regarding the social and economic pillars. A trend in the application of multi-criteria decision analysis (MCDA) to integrate results and facilitate decision- and policy-making processes was identified. Future studies could focus on the integration between LCSA other methods, identify solutions for the system boundaries interaction across sustainability dimensions, and develop further case studies, specially by combining LCSA and MCDA. [ABSTRACT FROM AUTHOR]

Purpose: This paper analyses the voice of customers (VoCs) using a hybrid clustering multi-criteria decision-making (MCDM) approach. The proposed method serves as an efficient tool for how to approach multiple decision-making involving a large set of countrywide customer complaints in the Iranian automotive sector. Design/methodology/approach: The countrywide data comprising 3,342 customer complaints (VoCs) were gathered. A total of seven determinant complaint criteria were identified in brainstorming sessions with three groups (six each) of experts employing the fuzzy Delphi method. The weights of these criteria were assigned by applying the fuzzy best–worst method (FBWM) to identify the severity of the complaints. Subsequently, the complaints were clustered into five categories with respective customer locations (province), car type and manufacturer using the K-mean method and further prioritised and ranked employing the fuzzy complex proportional assessment of alternatives (FCOPRAS) method. Findings: The results indicated that the majority of complaints (1,027) from the various regions of the country belonged to one specific model of car made by a particular producer. The analyses revealed that only a few complaints were related to product quality, with the majority related to service and financial processes including delays in automobile delivery, delays in calculating monthly instalments, price variation, failure to provide a registration (licence) and failure to supply the agreed product. The proposed method is an efficient way to solve large-scale multidimensional problems and provide a robust and reliable set of results. Practical implications: The proposed method makes it much easier for management to deal with complaints by significantly reducing their number. The highest-ranked complaints from customers of the car industry in Iran are those related to delivery time, price alternations, customer service support and quality issues. Surveying the list of complaints shows that paying attention to the four most voiced complaints can reduce them more than 54%. Management can make appropriate strategies to improve the production quality as well as business processes, thus producing a significant number of customer complaints. Originality/value: This paper proposes a comprehensive approach to critically analyse the VoCs by combining qualitative and decision-making approaches including K-mean, FCOPRAS, fuzzy Delphi and FBWM. This is the first paper that analyses the VoCs in the automotive sector in a developing country's context involving large-scale decision-making problem-solving. [ABSTRACT FROM AUTHOR]

Multiple criteria decision-making (MCDM) has experienced significant growth in recent years, owing to its capacity to integrate even contradictory criteria. This study conducted a comprehensive literature review of MCDM for assessing, selecting, and retrofitting buildings. The bibliometric search used a search algorithm in specialized databases. A filtering and expansion process was done by reviewing references, and 91 relevant articles were selected. The analysis revealed that in a group of studies, socioeconomic criteria were used to assess the vulnerability of buildings. On the other hand, some research integrated the three dimensions of sustainability (economic, social, and environmental) along with safety considerations when identifying optimal retrofit alternatives. Classic MCDMs are prevalent in research within this field. Among the most used methods, the Analytic Hierarchy Process (AHP) was employed for criteria weighting, Simple Additive Weighting (SAW) for constructing vulnerability indices, and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for building retrofitting. This literature review contributes to the path toward a holistic renovation of the existing building stock, providing recommendations for future research to improve decision-making solutions for integrating the safety and sustainability of existing buildings. [ABSTRACT FROM AUTHOR]

The crop-land suitability assessment (LSA) is important for managing land and water resources and developing sustainable agricultural systems. In the field of determining the suitability of cropland, the multi-criteria evaluation approach (MCEA) or multi-criteria decision-making (MCDM) is becoming more popular as a tool for analyzing difficult situations and obtaining logical conclusions. The 75 relevant publications from 2010 to 2023 were reviewed and summarized in this paper to precisely explain and identify MCEA application areas and decision-making problems resolved within the crop-land suitability assessment. The findings indicated that the MCDM or MCEA techniques have been applied with or without remote sensing, Agricultural Land Use Evaluation System, parametric methods, etc. for land suitability evaluation. This study also contributes to the classification of criteria used for this purpose. A total of 117 parameters from six groups: soil properties, climate, topography, hydro-geomorphology, land use compatibility, and hazard are necessary for LSA. [ABSTRACT FROM AUTHOR]

Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision-making methods such as the Analytic Hierarchy/Network Process (AHP/ANP), the Best-Worst method (BWM), PROMETHEE and many others. Pairwise comparisons can be performed within several frameworks such as multiplicative, additive and fuzzy representations of preferences, which are particular instances of a more general framework based on Abelian linearly ordered groups. Though multiplicative, additive and fuzzy representations of preferences are widely used in practice, it is unknown whether decision makers are equally precise in the three aforementioned representations when they measure objective data. Therefore, the aim of this paper is to design, carry out and analyse an experiment with over 200 respondents (undergraduate university students) from two countries, Czechia and Italy, to compare precision of the respondents in all three representations. In the experiment, respondents pairwise compared (by approximation) the areas of four geometric figures and then, the imprecision of their assessments was measured by computing the distance with the exact pairwise comparisons. We grouped the respondents in such a way that each participant was allowed to deal with a unique type of representation. The outcomes of the experiment indicate that the multiplicative approach is the most precise. [ABSTRACT FROM AUTHOR]

Multiple Criteria Decision Analysis (MCDA) sorting models are highly relevant for solving real-world problems. Thus, in the literature, the great majority of MCDM methods tackled the choice or ranking problems unlike the sorting approaches although assigning alternatives to predefined homogeneous categories (classes) presents a complex problem. Thus, in this paper, we tackled the sorting problematic using the EDAS "Evaluation based on Distance from Average Solution" method. It is used for ranking alternatives, in a decreasing order, according to their Appraisal Scores (AS). Nevertheless, the current version of EDAS method cannot deal with sorting problems. Since a great majority of real-world decision-making problems are modeled as sorting ones, we proposed a new sorting MCDM method called EDAS-Sort to cope with decision problems requiring assigning alternatives to predefined and ordered classes. Given that we dealt with classes defined by their boundary profiles, the proposed method is called EDASSort-B. To demonstrate and underline it, we presented a case study on a bank agency located in Sfax, Tunisia which aims to assign clients requesting loans to three predefined and ordered categories: very solvent, solvent, and doubtful according to various criteria. Therefore, the head of the bank agency (decision maker) will gain insight on the client's profile and whether he is trustful or not to repay the loan. Thus, the EDAS-Sort-B is effective for solving problems requiring assigning alternatives to predefined and ordered categories. Thereupon, the main advantage of EDAS-Sort-B is to help the DM "Decision Maker" to take a real-time decision related to alternatives' assignment. [ABSTRACT FROM AUTHOR]

Natural disasters such as earthquakes endanger human lives and infrastructure, particularly in urban areas. With the advancements in science and technology in understanding natural hazards, recent studies have attempted to mitigate them by mapping the risks using geospatial technology. In this paper, we attempt to integrate the multi-criteria decision-making (MCDM) models, namely the Analytical Hierarchy Process (AHP) and the Criteria Importance Through Inter-criteria Correlation (CRITIC), besides using the artificial neural network (ANN) to assess the seismic risk in the eastern coast of India. The AHP-CRITIC technique is used to evaluate the earthquake coping capacity and vulnerability and has been further used to generate a training base for earthquake probability mapping by ANN. The earthquake probability and spatial intensity information are used to develop the hazard map. Following that, integrating vulnerability, hazard and coping capacity spatial information assessed earthquake risk. Our results indicate that approximately 5% of the study area is at high risk, whilst more than 11% of the population is at high risk due to seismic induced hazards. The area under the curve of the receiver operating characteristic curve is 0.85, which indicates reliable results. The results of this study may help various agencies involved in planning, development and disaster mitigation to develop seismic hazard mitigation methods by better understanding their impacts on the eastern coastal region of India. [ABSTRACT FROM AUTHOR]

Decision-Making (DM) is one of the most important components of human cognition. Starting with a review of the traditional criteria for DM, this work presents also a method for the verification of a decision, a step of the DM process which, due to its special interest, is usually examined separately from its other steps. Frequently in everyday life, however, the data of a DM problem are vague and characterized by uncertainty. In such cases the traditional techniques for DM, which are based on principles of the bivalent logic (yes-no), cannot help effectively in making the right decision. The first who introduced principles of the fuzzy sets theory in DM were Bellman and Zadeh in 1970 and an example is given here illustrating their fuzzy criterion for DM. Also, among the several fuzzy methods proposed later by other researchers for a more effective DM, a hybrid method is developed here for parametric multiple-criteria DM using soft sets and grey numbers (or intuitionistic fuzzy sets, or neutrosophic sets) as tools, which improves an earlier method proposed by Maji et al. in 2002. All the DM approaches presented in this paper are illustrated with everyday practical examples. [ABSTRACT FROM AUTHOR]

The impact of climate change, including fires, droughts and storms, on natural resources and agricultural output is increasing. In addition to these problems, resource depletion and greenhouse gas (GHG) emissions, agriculture also contributes to global warming. To reduce the dangers of climate change, farmers are using sustainable practices. This article aims to link agri‐food 4.0 technology with climate‐smart agriculture (CSA) to lessen the two‐way interaction (both affecting and impacted) between the agricultural sector and global warming, as well as dangers related to the agri‐food business. In light of this information, the research methodology of the paper is twofold. Initially, related risks towards climate change and the CSA and agri‐food 4.0 technologies to overcome these risks were determined through a literature review. Then, risks and technologies are evaluated by adopting the TODIM (an acronym in Portuguese for Interactive and Multicriteria Decision Making), which is used for evaluating the criteria set with the related technologies to overcome climate change‐related risks and provide a guiding map for academics and practitioners to eliminate risks associated with these climate change‐related factors. According to the study's findings, the highest‐priority concerns in the agri‐food industries that are connected to climate change include energy consumption, food safety and GHG emissions. Internet of Things (IoT), bio‐innovation and artificial intelligence are thought to be the most promising technological solutions to address these problems. [ABSTRACT FROM AUTHOR]

Global warming, climate change, and social problems are the worst human-induced sustainability issues that economies across the globe have witnessed. Water pollution, greenhouse effect, poor working conditions, child labour and lack of coordination among channel partners have caused the considerable interruptions in the supply chain network. The purpose of the paper is to identify critical factors affecting behavioural and sustainable supply chain coordination and evaluate strategies for risk reduction in the supply chain coordination in the context of digitization. This study purposes a novel supply chain coordination framework which consists of four themes such as system, actor, objective and action on which the success or the failure of supply chain can be contingent. Our study integrates multi-criteria decision approach using Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) and Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy-DEMATEL) to investigate factors that affected the behavioural and sustainable supply chain coordination in the context of digitization. The Fuzzy-AHP method qualified to hierarchically rank the factors based on the relative fuzzy weightage while Fuzzy-DEMATEL established the inter-relationships among the factors and classified them into cause and effect groups. The findings of our study identified the Environmental performance and decarbonization as the most significant factor and the speed to market as the least important factor in developing behavioural and sustainable supply chain coordination in the context of digitization. Our analysis from Fuzzy AHP-DEMATEL approach reveal that the social preferences (power balance, reciprocity, fairness) is a significant causal factor which can effectively abolish the issues plaguing behavioural and sustainable supply chain coordination in the context of digitization. The results from our study aim to facilitate decision makers in cultivating a sustainable supply chain framework that can boost trust among the channel partners environmental performance, social performance and channel efficiency of the supply chain, thereby ensuring sustainability and socio welfare of all the supply chain. [ABSTRACT FROM AUTHOR]

Plithogenic sets coined by Smarandache in the year 2018 has unveiled new research opportunities in the field of Multi criteria decision making (MCDM). The contributions and developments of new decision making approaches based on plithogeny is gaining high momentum presently. The theoretical conceptualization of different phenomenon with plithogenic sets are also applied in designing optimal solutions to the decision making problems. This review paper presents the applications of plithogenic MCDM from the year 2018 to till date in almost all the spheres of decision making scenario. The literature works of the researchers presented in this paper will certainly portray the compatibility and flexibility of plithogenic sets, operators and other decision making tools. Though the time span considered for counting on the plithogeny based works is short, the applications of plithogenic sets are growing many in number and also plithogeny based theories are amplifying in a speedy manner. This has motivated the authors to investigate on the proliferation of plithogeny applications in decision making. This review paper has focused on the dimensions of different fields to which plithogeny is applied, new plithogeny based theories, extension of plithogeny, plithogenic based operators and measures. In addition to it the data on the publications of plithogeny based articles and interests of researchers are also presented as a part of this review work. The overall impact of plithogeny in the arena of decision making science and on the researchers of the same field is well sketched in this paper with the intention and hope of inspiring plithogenic researchers. [ABSTRACT FROM AUTHOR]

Municipal solid waste (MSW) development has increased on a global scale, posing significant socio-economic and environmental challenges. Waste to energy conversion is strategic because it can determine the best waste-to-energy technology. Recognizing the significance of waste in energy selection, this research aims to select the best technology based on its eco-friendliness. A two-phase methodology is used for presenting a framework for waste to energy technology selection. The first phase involves the selection of criteria for this problem and the perspectives of decision makers. Ranking the selected criteria using a novel SWARA method, and ranking the technology of WtE with respect to selected criteria weights are obtained. In this paper, we investigate the WtE technology problem using the novel concept of the Pythagorean Neutrosophic fuzzy set (PNFS). This set is a hybrid of the Pythagorean and Neutrosophic fuzzy sets. In this paper, we propose the best WtE technology for India. We employ the MULTIMOORA method in the Pythagorean Neutrosophic fuzzy environment for this purpose. Sensitivity and comparison analyses are also performed to ensure the framework's robustness. The findings of this study are useful in ranking the technology, and as a result, waste management can replicate the proposed framework for waste disposal for their new platform. [ABSTRACT FROM AUTHOR]

Microemulsion fuels, also known as surfactant-free fuels, are fuels made from a combination of two immiscible liquids, hydrocarbon fuel, and water, with a trace quantity of a co-solvent. Surfactants are often used in conventional microemulsion fuels, however surfactant-free microemulsion fuels instead depend on the thermodynamic features of the combination to generate a stable emulsion. In this paper, the multi-criteria decision-making (MCDM) model for choosing microemulsion fuel with surfactant-free. Various helpful and harmful criteria were evaluated for ten fuels at varying motor loads, according to performance and emission characteristics. This paper integrated the neutrosophic set with the TOPSIS method. The neutrosophic set is used to deal with uncertain data. The TOPSIS method is used to rank the different fuels. [ABSTRACT FROM AUTHOR]

Requirement prioritization (RP) is a crucial task in managing requirements as it determines the order of implementation and, thus, the delivery of a software system. Improper RP may cause software project failures due to over budget and schedule as well as a low-quality product. Several factors influence RP. One of which is requirements dependency. Handling inappropriate handling of requirements dependencies can lead to software development failures. If a requirement that serves as a prerequisite for other requirements is given low priority, it affects the overall project completion time. Despite its importance, little is known about requirements dependency in RP, particularly its impacts, types, and techniques. This study, therefore, aims to understand the phenomenon by analyzing the existing literature. It addresses three objectives, namely, to investigate the impacts of requirements dependency on RP, to identify different types of requirements dependency, and to discover the techniques used for requirements dependency problems in RP. To fulfill the objectives, this study adopts the Systematic Literature Review (SLR) method. Applying the SLR protocol, this study selected forty primary articles, which comprise 58% journal papers, 32% conference proceedings, and 10% book sections. The results of data synthesis indicate that requirements dependency has significant impacts on RP, and there are a number of requirements dependency types as well as techniques for addressing requirements dependency problems in RP. This research discovered various techniques employed, including the use of Graphs for RD visualization, Machine Learning for handling large-scale RP, decision making for multi-criteria handling, and optimization techniques utilizing evolutionary algorithms. The study also reveals that the existing techniques have encountered serious limitations in terms of scalability, time consumption, interdependencies of requirements, and limited types of requirement dependencies. [ABSTRACT FROM AUTHOR]

Supply chain management (SCM) encompasses a wide variety of decision-making problems that affect business and supply chain performance. Since most of these problems involve uncertainty and hesitation on the part of decision makers (DMs), various studies have emerged recently that present SCM applications of techniques based on Hesitant Fuzzy Linguistic Term Sets (HFLTSs) and HFLTS extensions. Given the relevance of this subject and the lack of literature review studies, this study presents a systematic review of HFLTS and HFLTS extension applications to SCM decision-making problems. In order to answer a set of research questions, the selected papers were classified in accordance with a group of factors that are pertinent to the origins of these studies, SCM, HFLTSs, and decision making. The results demonstrated that the Source and Enable processes have been studied with greater frequency, while the most common problems have to do with supplier selection, failure evaluation, and performance evaluation. The companies of the automotive sector predominated in the analyzed studies. Even though most of the studies used techniques based on HFLTSs, we identified applications of seven distinct HFLTS extensions. The main contribution of this study consists of presenting an overview of the use of HFLTSs and their extensions in practical examples of SCM, highlighting trends and research opportunities. It is the first study to analyze applications of decision-making techniques that deal with hesitation in SCM. Therefore, the results can help researchers and practitioners develop new studies that involve the use of HFLTSs and HFLTS extensions in decision-making problems, given that this study systematizes elements that should be considered in the modeling, application, and validation of these methods. [ABSTRACT FROM AUTHOR]

Pythagorean cubic fuzzy sets (PCFSs) are a more advanced version of interval-valued Pythagorean fuzzy sets where membership and non-membership are depicted using cubic sets. These sets offer a greater amount of data to handle uncertainties in the information. However, there has been no previous research on the use of Einstein operations for aggregating PCFSs. This study proposes two new aggregator operators, namely, Pythagorean cubic fuzzy Einstein weighted averaging (PCFEWA) and Pythagorean cubic fuzzy Einstein ordered weighted averaging (PCFEOWA), which extend the concept of Einstein operators to PCFSs. These operators offer a more effective and precise way of aggregating Pythagorean cubic fuzzy information, especially in decision-making scenarios involving multiple criteria and expert opinions. To illustrate the practical implementation of this approach, we apply an established MCDM model and conduct a case study aimed at identifying the optimal investment market. This case study enables the evaluation and validation of the established MCDM model's effectiveness and reliability, thus making a valuable contribution to the field of investment analysis and decision-making. The study systematically compares the proposed approach with existing methods and demonstrates its superiority in terms of validity, practicality and effectiveness. Ultimately, this paper contributes to the ongoing development of sophisticated techniques for modeling and analyzing complex systems, offering practical solutions to real-world decision-making problems. [ABSTRACT FROM AUTHOR]

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Traffic safety is an area of great importance, since there are many traffic accidents every day in which a significant number of people are killed. Defining certain strategies and identifying potentially the most dangerous towns and cities regarding this area are, on the one hand, a necessity, and, on the other hand, a challenge. In this paper, integrated Multi-Criteria Decision-Making (MCDM) model for ranking cities in Libya from the aspect of traffic safety has been proposed. The model implies a set of 8 criteria on the basis of which 5 decision-makers rated the 10 most deprived cities in Libya. The Full Consistency Model (FUCOM) in combination with the rough Dombi aggregator is used to determine the significance of the criteria. The Rough Simple Additive Weighting (R-SAW) method is used to rank the alternatives. The rough Dombi aggregator is also used for averaging in group decision-making while evaluating the alternatives. The stability of the model and the obtained results has been verified by the sensitivity analysis, which implies a 2-phase procedure. In the 1st phase, rough Additive Ratio Assessment (R-ARAS), Rough Weighted Aggregated Sum Product Assessment (R-WASPAS), Rough Complex Proportional Assessment (R-COPRAS) and Rough Multi-Attributive Border Approximation-area Comparison (R-MABAC) methods are applied. The 2nd phase implies changing the parameter ρ in the procedure of rough Dombi aggregator, while the 3rd phase includes the calculation of Spearman’s Correlation Coefficient (SCC) that shows a high correlation of ranks. [ABSTRACT FROM AUTHOR]

In a cloud environment, consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost. On the other hand, Cloud Service Providers (CSPs) seek to maximize their profits by attracting and serving more consumers based on their resource capabilities. The literature has discussed the problem by considering either consumers' needs or CSPs' capabilities. A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task scheduling in a more efficient way. The paper proposes a model that adopts a Multi-Criteria Decision Making (MCDM) method, called Analytic Hierarchy Process (AHP), to acquire the information of consumers' preferences and service providers' capabilities to prioritize both tasks and resources. The model also provides a matching technique to assign each task to the best resource of a CSP while preserves the fairness of scheduling more tasks for resources with higher capabilities. Our experimental results prove the feasibility of the proposed model for prioritizing hundreds of tasks/services and CSPs based on a defined set of criteria, and matching each set of tasks/services to the best CSPS. [ABSTRACT FROM AUTHOR]

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

Mass casualty incident (MCI) is an unpredictable situation where a great number of people have been injured after an accident or sudden disease. Survival of the injured in the MCI depends on the efficiency of the directed emergency system (DES). The organization and management of medical assistance is of paramount importance. The shortest possible time to provide medical services to injured persons is crucial. The medical service in the case of the MCI primarily requires decisions on the priority of the order of treatment of the injured, the choice of medical transport and the location of specialized emergency treatment. As part of this paper, the effectiveness of the DES has been analyzed, and criteria used to improve rescue operations have been formulated. A formalized mathematical description of the medical rescue operations in MCIs has been proposed, and the optimization problem as the mixed integer linear programming (MILP) task was formulated. Optimization of an example case of rescue operations in MCIs has been presented. A computer simulator for optimal decision-making in medical rescue operations (CSMRO) has been developed for this purpose. The CSMRO implements various multi-criteria optimization methods to solve the formulated problem of rescue operations optimization. The results of computations made with the developed CSMRO simulator significantly shorten the time of decision-making in mass casualty incident handling. [ABSTRACT FROM AUTHOR]

Sustainability policy evaluation and assessment seeks to answer the key question, sustainability of what and whom? Consequently, sustainability issues are multidimensional in nature and feature a high degree of conflict, uncertainty and complexity. Social multi-criteria evaluation (SMCE) has been explicitly designed for public policies; it builds on formal modelling techniques whose main achievement is the fact that the use of different evaluation criteria translates directly into plurality of values and dimensions underpinning a policy process. SMCE aims at being inter/multi-disciplinary (with respect to the technical team), participatory (with respect to the community) and transparent. SMCE can help deal with three different types of sustainability-related policy issues: 1) epistemological uncertainty (human representation of a given policy problem necessarily reflects perceptions, values and interests of those structuring the problem); 2) complexity (the existence of different levels and scales at which a hierarchical system can be analyzed implies the unavoidable existence of non-equivalent descriptions of it both in space and time); and 3) mathematical manipulation rules of relevant information (compensability versus non-compensability, preference modelling of intensities of preference, mixed information on criterion scores, weights as trade-offs versus weights as importance coefficients, choice of a proper ranking algorithm). This paper focuses on the these three issues and provides an overview of the SMCE approaches to them. [ABSTRACT FROM AUTHOR]

In the fuzzy multicriteria decision-making approach, a committee of decision-makers is usually involved in the assessment of the suitability of different alternatives based on the evaluation criteria by using linguistic terms and their equivalent fuzzy numbers. In this context, researchers have developed the Pythagorean fuzzy set (PFS) to overcome the limitation of intuitionistic fuzzy set in the description of decision-maker information such as imposing restrictions on the representation of membership and nonmembership grades. On the one hand, PFS still does not have sufficient ability and flexibility to deal with such issues. On the other hand, multipolar technology is used to operate large-scale systems in real-life situations, especially in dealing with dissatisfaction and indeterminacy grades for the alternatives of the reference set. Thus, m-polar fuzzy set is utilized and applied with other fuzzy sets because of its remarkable ability as a tool for depicting fuzziness and uncertainty under multipolar information in many circumstances. With the practical features of m-polar fuzzy set in combination with PFS, this paper employs it to extend two considerable MCDM methods, namely, fuzzy decision by opinion score method and fuzzy-weighted zero inconsistency. Such extensions, called Pythagorean m-polar fuzzy-weighted zero-inconsistency (Pm-PFWZIC) method and Pythagorean m-polar fuzzy decision by opinion score method (Pm-PFDOSM), are formulated to weight the evaluation criteria followed by alternative ranking progressively. The research methodology is presented as follows. Firstly, the mechanisms of Pm-PFWZIC and Pm-PFDOSM are formulated and integrated into the development phase. Secondly, the description of the real-world case study of the evaluation and benchmarking of the sign language recognition systems is adapted and presented. The result of Pm-PFWZIC shows that the criterion of 'finger movements' has the highest weight amongst the rest of the criteria, whereas 'misclassification error' has the lowest weight. In the ranking results, a variation of ranking is scored by each expert, and group decision-making is applied to solve the individual ranking variety. The robustness of the formulated methods is evaluated using systematic ranking, sensitivity analysis and comparison analysis. [ABSTRACT FROM AUTHOR]

This paper introduces REDUCE, a Python module designed to minimize inconsistency in multiplicative pairwise comparisons (PC), a fundamental technique in Multi-Criteria Decision Making (MCDM). Pairwise comparisons are extensively used in various fields, including engineering science and numerical simulation methods, to compare different options based on a set of criteria. However, human errors in perception and judgment often lead to inconsistencies in pairwise comparison matrices (PCM). REDUCE addresses this issue by implementing several algorithms that identify and correct inaccurate data in PCMs, thereby reducing the inconsistency ratio. These algorithms do not require expert intervention, making REDUCE a valuable tool for both scientific research and small to medium enterprises that may not have access to costly commercial software or dedicated decision-making experts. The main functionality of the module is incorporating iterative algorithms for inconsistency reduction. The REDUCE library, written in Python and utilizing auxiliary libraries such as NumPy, SciPy, and SymPy, offers 21 functions categorized into data input helpers, consistency ratio (CR) reduction algorithms, PCM indexes, and support functions. Performance testing indicates that the library can efficiently handle matrices of varying sizes, particularly those ranging from 3x3 to 10x10, and its use significantly accelerates the process compared to spreadsheets, especially when dealing with large quantities of matrices. The library has already been used in several research papers and application tools, and its availability as a free resource opens up opportunities for small and medium-sized enterprises to leverage multi-criteria decision-making methods. Currently, there are no publicly available libraries for this solution. The authors believe that the proposed module may contribute to do better decision-making process in pairwise comparisons, not only for the circle of scientists but also for small and medium enterprises that usually cannot afford expensive commercial software and do not employ full-time experts in decision-making as they rely on the experience of their employees and free online resources. It should also contributes to the transition to Industry 4.0 and advances research in fields such as fuzzy logic, preference programming, and constructive consistent approximations. [ABSTRACT FROM AUTHOR]

This paper represents two stage fuzzy methodology for the optimal planning of order of establishment of temporary logistics hubs (TLHs). At the first stage, a q-rung orthopair fuzzy TOPSIS approach for formation and representing of expert's knowledge on the parameters of the order of establishment of temporary logistics hubs is developed, when resources (mobile storage units used as TLHs) are limited. At the second stage, based on the constructed fuzzy TOPSIS aggregation a new objective function is formulated. Constructed criterion maximizes TLHs' total identification level of the order of establishment. This criterion together with second criterion - minimization of number of selected TLHs', creates the multi-objective facility location set covering problem. Two stage approach is illustrated by the simulation example of emergency temporary logistics hubs' selection preferences identification for a city in Georgia. [ABSTRACT FROM AUTHOR]

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Simple Additive Weighting (SAW) are among the most employed approaches for aggregating performances in Multi-Criteria Decision-Making (MCDM). TOPSIS and SAW are two MCDM methods based on the value function approach and are often used in combination with other MCDM methods in order to produce rankings of alternatives. In this paper, first, we analyse some common features of these two MCDM methods with a specific reference to the additive properties of the value function and to the sensitivity of the value function to trade-off weights. Based on such methodological insights, an experimental comparison of the results provided by these two aggregation methods across a computational test is performed. Specifically, similarities in rankings of alternatives produced by TOPSIS and SAW are evaluated under three different Minkowski distances (namely, the Euclidean, Manhattan and Tchebichev ones). Similarities are measured trough a set of statistical indices. Results show that TOPSIS, when used in combination with a Manhattan distance, produces rankings which are extremely similar to the ones resulting from SAW. Similarities are also Experimental results confirm that rankings produced by TOPSIS methods are closer to SAW ones when similar formal properties are satisfied. [ABSTRACT FROM AUTHOR]

Multicriteria decision-making (MCDM) techniques have successfully been used to address a wide range of real-world decision-making issues. The best–worst method (BWM) is one of the several deterministic MCDM approaches. A recently proposed method called the multichoice best–worst method (MCBWM) takes into account several linguistic terms for pairwise comparisons of relative preferences among the criteria. It has been shown that the MCBWM approach has advantages over BWM: it reduces the calculation and determines optimal weight values by providing the choices for the optimal solution. This paper proposes a unique method for group decision-making based on MCBWM. We extended the MCBWM to solve group decision-making problems. A novel solution approach was developed and validated for multiple problems. Two examples and one case study were solved using the proposed approach to demonstrate the validity and application of the proposed method. The results were further compared with existing models to validate the proposed approach. We found that the obtained ranking order for all problems is the same and that the proposed model has a higher consistency ratio than the existing approaches. This method can be extended to other mathematical programming models for collective decision making in uncertain situations. [ABSTRACT FROM AUTHOR]

Urban development broadly impacts the hydrological cycle, leading to increased peak flow and flooding. Surface water detention ponds are among the most efficient measures for attenuating peak flow and returning it from development to pre‐development conditions. However, the major challenge is identifying optimal locations and cost‐effective designs for these ponds. This paper presents a new framework for identifying the best strategies for using detention ponds to control floods in urban drainage systems (UDS). The framework comprises a portfolio of simulation tools coupled with evolutionary optimisation and multi‐criteria decision analysis models. Hydraulic simulation of UDS is first modelled using SWMM and GIS tools. A multi‐objective optimisation model was used to find the optimal location and design for detention ponds. The compromise programming (CP) multi‐criteria decision‐making method was then used to prioritise potential best management solutions for detention ponds based on several sustainability criteria comprising economic, environmental, physiographic and social factors. The results identified the key features of potential detention ponds appearing in all multi‐objective optimal solutions that are useful for decision‐makers/designers when planning/designing for new detention ponds. The selected optimal pond strategies can significantly improve the UDS performance by decreasing flood damage between 66% and 90% at the cost of between $50,000 and $160,000. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) aims to revolutionize users’ daily lives by enabling seamless data exchange among various ubiquitous devices over the Internet. However, achieving this broad objective can pose significant challenges for applications that require synchronized timing, such as ensuring the temporal sequencing of data or synchronized performance of activities. IoT networks typically comprise entities with varying resources, making it challenging to implement existing time synchronization methods like N.T.P. (Network Time Protocol) on resource-constrained devices. On the other hand, solutions that work for constrained systems may not be scalable across diverse IoT deployments. This survey paper delves into the clock synchronization issues in IoT installations where applications require a unified perception of time. The article describes clock synchronization solutions for various models and their associated performance and discusses several research challenges related to clock synchronization. Additionally, a review of time synchronization techniques is provided to aid IoT practitioners in selecting the most relevant aspects for deployment. [ABSTRACT FROM AUTHOR]

Multi-criteria decision-making (MCDM) is the most widely used decision-making method to solve many complex problems. However, classical MCDM approaches tend to make decisions when the parameters are imprecise or uncertain. The concept of a complex fuzzy set is new in the field of fuzzy set theory. It is a set that can collect and interpret the membership grades from the unit circle in a plane instead of the interval [0,1]. CFS cannot deal with membership and non-membership grades, while complex intuitionistic fuzzy set and complex Pythagorean fuzzy set works only for a limited range of values. The concept of a complex Fermatean fuzzy set (CFFS) is proposed to deal with these problems. This paper presents the main ideas of CFFN and its properties are studied. The proposed new distance measures for real-world problems are also discussed. A comparative study of the proposed new work is also conducted. [ABSTRACT FROM AUTHOR]

In this paper, we show the practical application of two recently proposed Multi-Criteria Decision Analysis (MCDA) methods, namely the Stable Preference Ordering Towards the Ideal Solution (SPOTIS) and the Reference Ideal Method (RIM) methods. Both of these methods can utilize the Expected Solution Point (ESP) concept, which allows it to easily reflect the decision-maker's or the customer's preferences and expectations. We show the comparison of those methods in the practical study case of laptop choice for the customer with specific needs and expectations for the hardware expressed using ESP. The comparison also includes rankings built toward an optimal solution to underline the necessity of such an approach as the Expected Solution Point. We also use the recently developed Ranking Comparison (RANCOM) method to identify criteria weights to include customer preferences in the weights. The paper also contains a broad discussion of the obtained results and limitations of the presented methods. [ABSTRACT FROM AUTHOR]

In modern civilization, individuals are increasingly concerned with evaluating the quality of medical services. Evaluation of the quality of medical services enables medical care providers to monitor and improve their service quality. The evaluation of medical service quality is efficiently addressed by the novel concept of Aczel–Alsina operators in an intuitionistic hesitant fuzzy (IHF) environment as multicriteria decision-making (MCDM) problem. Thus, this paper presents the IHF Aczel–Alsina weighted geometric operators for IHF information. We first apply the Aczel–Alsina norms to IHF scenarios and present novel operations of intuitionistic hesitant fuzzy sets. This article develops a unique strategy for evaluating the quality of medical services based on the specified operators, including a quantitative framework for evaluating medical service quality and a novel MCDM technique. Finally, this article presents a numerical example of the novel approach used to evaluate medical services for hospitals and compares it to conventional MCDM methods to highlight the suggested superiority method. According to the comparative results, our strategy outperforms the insufficiency of lacking decision flexibility in the existing MAGDM method. [ABSTRACT FROM AUTHOR]