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Given the advances in technology and the development of urban development and progress in people's lifestyles, the use of bridges is considered as an important and necessary way of esophageal communication. Bridges are one of the most important tools for connecting roads and different cities, which connect different areas and create connections between people. One of the most important and necessary measures in the bridge industry is related to the repair and maintenance of bridges, which cost less than building a bridge and help to create connections between people. To this end, the present study examines the effects affecting the maintenance and repair of bridges in urban contexts and for this issue an approach under conditions of intuitive fuzzy uncertainty based on analytic network process and comprise solution methods to calculate weights and option ranking offers. However, an integrated group decision making-based soft computing approach is tailored by computing the criteria importance and experts' weights to solve the urban concrete bridge maintenance model selection problem. Finally, to validate the proposed method, a case study is used along with a comparison of the proposed method and existing methods in the literature. The final results indicate the strength and efficiency of the proposed method in calculating weights and ranking options for the project of maintenance and repair of urban bridges in Rasht. [ABSTRACT FROM AUTHOR]

Compared with intellectualization, lean is what family small- and medium-sized enterprises (SMEs) should pay more attention to and complete. Lean management implementation (LMI) can lead to better performance, but can be detrimental to non-economic goals, such as socioemotional wealth (SEW) associated with family control. The contradiction between economic goals and non-economic goals makes LMI become a multi-criteria decision-making problem in family SMEs. To address this problem, we propose an evaluation model combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based Analytic Network Process (DANP), and Viekriterijumsko Kompromisno Rangiranje (VIKOR) method. The evaluation model can be used to evaluate and select the optimal lean management scheme that meets the SEW preferences and lean management preferences of family SMEs. Moreover, the evaluation model can also be used to provide targeted improvement suggestions for LMI to improve innovation performance. We construct an evaluation framework based on practical criteria from both lean tools and SEW carriers. These practical criteria can correspond to the activities and goals of the LMI, ensuring the usefulness of the evaluation model. In addition, taking a family SME as an example, we conducted case analysis and sensitivity analysis to verify the evaluation model. The study results provide an important reference for family SMEs to implement lean management. [ABSTRACT FROM AUTHOR]

Railways are the backbone of complex and multimodal transport systems in Europe. To secure a larger share of the transport market and attract existing and future freight customers, further improvement in services is required. To achieve this goal, the use of new technologies in the era of railway automation and digitalization is required. Automatic train operation (ATO) in rail transport is considered a promising solution for providing cost-effective rail products. In this study, we define ATO as autonomous train operation and the feasibility of ATO deployment in rail freight is investigated. For this purpose, a knowledge-based approach is introduced to identify opportunities, problems, and the most appropriate grade of automation in rail freight. In a multi-stage process, Delphi questionnaires were combined with the analytic network process (ANP) method to investigate, define, and weight the determinants for ATO deployment. The final phase of the survey estimated the potential costs and drivers for different grades of automation. The results show that, in addition to the positive impacts of ATO, there are numerous challenges and risks that need to be analysed before ATO is implemented. In addition, the Delphi-ANP approach was used to identify the key determinants for decision-making prior to ATO implementation and the most viable alternative based on them. Investment cost, level of safety, energy saving, and reliability of management system are the most important determinants for the decision to implement ATO. The results of this study can effectively support rail infrastructure managers and operators in strategic planning and decision-making for ATO implementation in rail freight. [ABSTRACT FROM AUTHOR]

With the advancement of technology and digital transformation almost everything is online. Social media business has become a trend in the modern-day industry. Business owners do not have faith in business digitization as they think it is expensive and time-consuming which cannot be substituted by approaches of conventional marketing. With the passage of time, internet marketing, digital transformation, social medial, and so on are becoming popular. Digital transformation has become meaningful but people do not know the importance of social media. The use of social media in the digital era and modern-day industry has become a concrete way of motivating the exchange of information within the social sphere. Social media has different aspects like people for expressing themselves, having fun, communicating, and many others. Social media are becoming popular with individuals and people are sometimes using them to benefit their own businesses. Social media is becoming a wide-range marketing platform for identifying consumers with improved aspects of business leading the band promotion benefits with the audience. Decisions at an early stage about the role of online media in business become one of the burning issues of modern industry which can benefit the business of the organization. The proposed study has presented the research in two-phase, the first one is to show the existing literature with different analyses, and in the second phase, the role of online media in business is evaluated through the Analytic Network Process. The results of the process showed better performance and applicability of the proposed approach. [ABSTRACT FROM AUTHOR]

Regression testing is a testing method conducted to ensure that improvements do not affect the software's current behavior. Test cases play a significant role in software testing activities since it detects faults in the software. The selection of test cases for execution based on the priority is a considerable decision-making step since testing needs to be carried out with limited computing resources like cost, effort, and time. Prioritized selection of test cases involves considering specific test case parameters or criteria; prioritizing test cases can be conceived as a multi-criteria decision-making problem. In this paper, using the Analytic Hierarchy Process (AHP) method, we suggest an approach for prioritizing the selection of the test cases. AHP provides a rational framework for structuring a decision-making problem. It is used to determine the priority of a set of criteria and to calculate the consistency ratio of those criteria using pair-wise comparisons of various measures. Using a new priority regression test algorithm proposed in this study, regression test prioritization is transformed into a multi-criteria decision-making problem. The suggested strategy has a higher Average Percentage of Faults Detected (APFD) value when many determinants are taken into account. The experimental results indicate that our proposed prioritization approach would improve the probability that faults will be detected early and enhance performance compared to other prioritization strategies. [ABSTRACT FROM AUTHOR]

Increasing competition as a result of globalization has forced the businesses to increase efficiency by focusing on the core competencies. This led businesses to outsource logistics. As a result, most of the businesses started to use third-party logistics (3PLs). There are various and conflicting criteria involved in 3PL selection, thus the selection of 3PL is a complex task for businesses. There are several methods in the literature used for 3PL selection, most of them are multi-criteria decision-making methods. A new hybrid model including Rough step-wise weight assessment ratio analysis (SWARA), Rough preference selection Index (RPSI), and Rough improved operational competitiveness rating analysis (IOCRA) has been used to select optimal third-party logistics providers in this study. There are two contributions to this study. First one is the development of a new hybrid rough model for 3PL selection. Second one is addressing the 3PL selection decision problem with newly developed Rough PSI and Rough IOCRA methods. Using this model and conducting a comprehensive analysis, the best option as a 3PL provider may be determined as a partner for logistics. The model effectiveness has been tested in a real case with a textile business and several 3PL providers. [ABSTRACT FROM AUTHOR]

Nontraditional manufacturing processes (NTMPs) bring the processing capabilities such as machining high strength and hard materials with desired accuracies and surface finish to the manufacturing companies. Therefore, there has been a significant increase in the use and number of NTMPs. Hence, choosing a particular NTMP for a specific application turns out to be a complex decision-making problem, which involves conflicting qualitative and quantitative ranking criteria. In recent NTMP ranking literature, it is noted that fuzzy approaches are better suited for handling uncertainties and incomplete information that exist within the NTMP ranking environment. This paper introduces such a fuzzy approach using the hesitant fuzzy preference selection index (PSI) method for the assessment of the criteria weights and the hesitant fuzzy correlation coefficient principle for ranking and recommending the most appropriate NTMP for a specific application. The proposed methodology and its efficiency in dealing with incomplete information under the fuzzy decision-making environment are explored with a case study. As a result of the study, the proposed model preferred the electron beam machining (EBM) as the most suitable nontraditional manufacturing process. On the other hand, triangular fuzzy TOPSIS methods offered the electrochemical machining (ECM) as the best choice among the alternatives. The differences among the ranking decisions are also analyzed in the paper. It can be concluded from the authors' various applications of the proposed hesitant fuzzy PSI method that it is extremely effective in representing fuzzy decision-making environments in NTMP ranking decisions. [ABSTRACT FROM AUTHOR]

Companies collect their used products and use them again to enhance their environmental and social profiles besides obtaining profit from using them again in the forward flow. By adding collecting and handling products at the end of their lifecycle in the context of reverse logistics, companies create closed-loop supply chains. The processes of a network can be sustainably optimized by adjusting the performance of its different facilities regarding sustainability dimensions. In circumstances that there is more than one facility on a specific level, they can be prioritized by different means such as multi-criteria decision-making or risk assessment techniques. In evaluating facilities with each method, some criteria might not be addressed appropriately, so combining these methods can produce a satisfactory answer. In this study, the performance level of each collection center regarding the sustainability of their performance and the risk associated with their operations in a reverse steel supply chain is evaluated. For this aim, the Failure Mode and Effects Analysis, Fuzzy Analytic Network Process, and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution have been integrated. The main contribution of this study is addressing the performance level of collection centers, as a vital facility in reverse logistics, from both operational and risk aspects considering sustainability dimensions. The applicability of the suggested methodology is demonstrated through its application in a steel manufacturer in the north of Iran, and the required sensitivity analyses are presented. Finally, managerial insights are discussed to enhance the performance of collection centers. [ABSTRACT FROM AUTHOR]

Weight determination is a popular research issue in the field of multicriteria analysis. Well-known approaches include the analytic hierarchical/network process (AHP/ANP), ratio method, Delphi method, etc., and other modifications and extensions have been proposed to address situations that are more complicated, e.g., fuzzy, grey, etc. Generally speaking, the ANP is the most popular method and derives the weights of criteria by considering interdependent and feedback effects. However, a problem with ANP is the cumbersome process of calculating the weights of the network relationships between criteria. More critical problem with ANP is the issue of divergence when absorbing criteria exist. Although several methods, such as the DEMATEL-based ANP and diminishing utility decision model, have been proposed to address these issues, these approaches have several limitations. In this paper, we propose a novel way to overcome the limitations of the above approaches and provide a possible solution for determining the weights of criteria via network influence maps (NetIM) with pseudonodes. The results of the numerical examples show NetIM is more rational, flexible, and useful than other methods. [ABSTRACT FROM AUTHOR]

Three-dimensional (3D) printing presents numerous opportunities for improving rapid prototyping and mass customization. However, the existing methods for assessing the performance of a 3D printer are associated with several problems. To solve these problems, a fuzzy collaborative intelligence fuzzy analytic hierarchy process (FAHP) approach is proposed in this study for assessing the performance of a 3D printer. In the proposed methodology, the alpha-cut operations method is first applied to derive the fuzzy priority of each criterion for each decision maker. Based on the derived priorities, the fuzzy-weighted average is then computed to assess the overall performance of each 3D printer for each decision maker. Thereafter, fuzzy intersection is applied to aggregate the assessment results of the decision makers. Finally, the center-of-gravity method is applied to defuzzify the aggregation result. By using the proposed methodology, the consensus among decision makers can be guaranteed. The proposed fuzzy collaborative intelligence FAHP approach has been applied to a real case of 10 3D printers. The experimental results indicated that the accuracy of the proposed methodology is superior to that of the existing methods, which yielded different ranking results owing to the use of approximation. [ABSTRACT FROM AUTHOR]

Pavement is an important part of a road structure. Selection of road pavement type is one of the important challenges of decision making by highway administrators. The life-cycle cost analysis is one of the common tools to select the pavement type which considers economic criteria such as costs of construction, maintenance and rehabilitation, and user costs; however, noneconomic criteria are neglected. The inadequate selection of road pavement type tends to increase the pavement life-cycle cost and impacts both environmental and social parameters. In this study, a three-step hybrid model is proposed to solve this problem. Initially, the causal relationships of main criteria affecting the pavement type selection are determined using decision making trial and evaluation laboratory. Then, the weight and importance of criteria and sub-criteria are determined using fuzzy analytic network process. Finally, the ranking of pavement alternatives is carried out using a fuzzy technique for order preference by similarity to ideal solution. A real case study consisting of five different types of pavements including hot mix asphalt, stone mastic asphalt, jointed plain concrete pavement, roller compacted concrete pavement with hot mix asphalt overlay and continuous reinforced concrete pavement is used to show the validity of the proposed model. [ABSTRACT FROM AUTHOR]

Grounded in the signaling theory, the study aims to develop a model for evaluation of emerging industries. The integrated method is proposed to evaluate the emerging industries with DANP (DEMATEL-based Analytic Network Process) and MOORA (Multi-Objective Optimization on the basis of Ratio Analysis) methodologies based on interval type 2 fuzzy sets, respectively. The application is illustrated by considering cleantech, new generation of information technology, biology/biotechnology and high-end equipment manufacturing industries, three dimensions and 12 criteria. The novelties of the study lie in a set of criteria and alternatives for the signaling in emerging industries supported by the literature and suggest a hybrid decision-making model based on the type 2 fuzzy sets. The signaling determinants for emerging industries could be evaluated by the proposed interval type 2 hybrid decision-making approach more accurately. The results demonstrate that the firms, operating in emerging industries at the early stage of their development, have to put emphasis on the third-party endorsements and human capital criteria, aiming to attract external investors. The suggested method lets the external investors narrow their options in selecting emerging industries and select the most attractive industries or spread investments among the most attractive industries. [ABSTRACT FROM AUTHOR]

The megatrends within the industrial automation and global value chains expedited the adoption of "Industry 4.0 enabled by 5G" to comprehend extremely flexible and smart production systems. The pivotal challenge for the smart manufacturing leveraging on 5G is the seamless vertical handover and connectivity to a suitable network in accordance with the determined application. The existing literature reports numerous strategies to ensure "always best connected" paradigm but they suffer from a couple of limitations. The amateurish approach employed in these strategies propelled the development of an autonomous network selection model exploiting fuzzy analytical hierarchical process consolidated with the novel extended efficacy coefficient method-based Technique for Order Preference by Similarity to Ideal Solution. This article addresses the vertical handover execution under the circumstances of four typical 5G application scenarios, respectively, i.e. Tactile Internet, Bitpipe, Internet of Things and Internet Access for Regional Areas. The analytical results validated through the extensive simulation revealed that the proposed hybrid scheme is effective and efficient compared to other methods in terms of avoiding the unnecessary handover and the ranking abnormality issues. [ABSTRACT FROM AUTHOR]

This paper proposes fuzzy integral-based decision methods to identify the core factors and their relationships for smart homes product improvement. The dominance-based rough set approach was used to retrieve core attributes and obtain rough knowledge-based rules. The decision-making trial and evaluation laboratory (DEMATEL) technique was used to build an influential network relationship map, and influential weights were determined through the DEMATEL-based analytic network process. Subsequently, the inter-relationships among criteria were calculated. Finally, the fuzzy integral method was used to measure the plausible synergy effects among the criteria, evaluate/rank alternatives for smart homes, and then provide suggestions for product improvement. The main innovation is the use of rough knowledge-based rule retrieval procedures and fuzzy measures for exploring the synergy effects on smart home improvement. Three smart home products/systems were examined to illustrate their performance on each criterion for improvement planning. This study contributes knowledge to research on consumer adoption of smart homes and presents improvement strategies. [ABSTRACT FROM AUTHOR]

This paper presents an innovative method for solving Pythagorean fuzzy (PF) multicriteria group decision-making problems with completely unknown weight information about criteria using entropy weight model, linear programming (LP) and modified technique for ordering preference by similarity to ideal solution (TOPSIS). At first, a new distance measure for PF sets is defined considering their degree of hesitancy and based on weighted Hamming distance and Hausdorff metric. To handle the fuzziness in criteria weights, PF entropy weight model is used to find the initial weights of the criteria in PF format. Following the concept of TOPSIS, an LP model is constructed on the basis of the view point that the chosen alternative should have the smallest distance from the positive ideal solution and the largest distance from the negative ideal solution. Then, the LP model is utilized to find optimal weights of the criteria. Using the newly defined distance measure, entropy weight model and LP model, TOPSIS is extended in PF environments. The existing methods are able to find criteria weights in the form of crisp values only, whereas proposed method is able to obtain those weights in PF format. Thus, the proposed method can overcome the drawback in computing criteria weight for multicriteria group decision-making in PF environments and reduce the information loss significantly. Several numerical examples are considered and solved to validate the superiority of the proposed methodology. [ABSTRACT FROM AUTHOR]

The extensions of ordinary fuzzy sets such as intuitionistic fuzzy sets, Pythagorean fuzzy sets, and neutrosophic sets, whose membership functions are based on three dimensions, aim at collecting experts' judgments more informatively and explicitly. In the literature, generalized three-dimensional spherical fuzzy sets have been introduced by Kutlu Gündoğdu and Kahraman (J Intell Fuzzy Syst 36(1):337–352, 2019a), including their arithmetic operations, aggregation operators, and defuzzification operations. In this paper, our aim is to extend classical analytic hierarchy process (AHP) to spherical fuzzy AHP (SF-AHP) method and to show its applicability and validity through a renewable energy location selection example and a comparative analysis between neutrosophic AHP and SF-AHP. [ABSTRACT FROM AUTHOR]

Providing better hospital service quality is one of the major concerns of healthcare industry in the world. Since health services in Turkey are provided in a very competitive environment, for making a better choice, the services delivered by the public and private hospitals should be evaluated according to the viewpoint of stakeholders in terms of satisfaction. In this study, a model proposal is presented based on the concept of Pythagorean fuzzy analytic hierarchy process and Pythagorean fuzzy technique for order preference by similarity to ideal solution method to provide an accurate decision-making process for evaluating the hospital service quality. We study under fuzzy environment to reduce uncertainty and vagueness, and use linguistic variables parameterized by Pythagorean fuzzy numbers. The proposed approach is separated from others with the integration of the methods in a way providing a systematic fuzzy decision-making process. A case study including 32 service quality criteria and two public and one private hospitals in Turkey assessed by 32 evaluators by medical staff, hospital executives, auxiliaries, and patients is performed to demonstrate the applicability and validity of the proposed approach. On conclusion, integrated model produces reliable and suggestive outcomes better representing the vagueness of decision-making process. [ABSTRACT FROM AUTHOR]

Multiplicative preference relation (MPR) is an efficient and widely used tool in describing the preferences of decision makers. The hesitant multiplicative preference relation (HMPR), as an extension of the MPR, is commonly used in collecting and representing all hesitant preferences and judgements of the decision makers. Considering that there usually appear some random or illogical preference degrees in the process of constructing the HMPRs, so it is necessary to derive a pithy preference relation (such as MPR) from the original HMPR through selecting the most proper and abandoning improper preference degrees, at the same time, the derived MPR is with the advantage of both terseness and the best consistency. Based on the multiplicative consistency measure of HMPRs, this paper proposes two regression methods to transform the HMPR into MPRs (called reduced MPRs). With the error analysis, the first proposed regression method provides some steps to not only extract the reduced MPRs from original HMPR but also calculate the consistencies of both the HMPR and the reduced MPRs. A case study reflects that the reduced MPR is with the highest consistency degree among those possible separated MPRs from HMPR. To apply this method to solve practical problems conveniently, a group decision-making procedure with hesitant multiplicative information is further given based on the first regression method. Time complexity comparison between our proposed method and an existing method indicates the effectiveness of our method. In addition, according to the weak consistency, we develop the second regression method and design an algorithm to obtain the reduced MPRs from the HMPR. Furthermore, we provide a method to check the weak consistency of the HMPR and repair the inconsistent one. Numerical examples verify that the second regression method proposed in this paper is an effective technique for checking the weak consistency and modifying the inconsistency HMPR to the one with weak consistency. [ABSTRACT FROM AUTHOR]

Several cloud services with comparable functionality are now available to customers at different prices and performance levels. Often, there may be trade-offs among different functional and non-functional requirements fulfilled by different cloud providers. Hence, it is difficult to evaluate the relative performances of the cloud services and their ranking based on various quality of service attributes. In this paper, we propose a modified data envelopment analysis and a modified super-efficiency data envelopment analysis for evaluating the cloud services and their efficiencies considering user preferences. We compare these methods of cloud service selection based on sensitivity analysis, adequacy to changes in DMUs, adequacy to support decision making and modeling of uncertainty. The comparison helps customers to choose a cloud service that is most suitable to their requirements and also creates a healthy competition among the cloud service providers. [ABSTRACT FROM AUTHOR]