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The paper aims to introduce a novel concept to solve the bi-level multi-criteria nonlinear fractional programming (BL-MCNFP) problems. Bi-level programming problem (BLPP) is rigorously flourished and studied by several researchers, which deals with decentralized decisions by comprising a sequence of two optimization problems, namely upper and lower-level problems. However, on the other hand, many real-world decision-making problems involve multiple objectives with fraction aspects, called fractional programming problems that reflect technical and economic performance.

This paper introduces a VIKOR (“VlseKriterijumska Optimizacija I Kompromisno Resenje”) approach to solve the BL-MCNFP problem. In this approach, an aggregating function based on L_P metrics is formulated on the basis of the “closeness” scheme from the “ideal” solution. The three steps perform the solution process: First, a new concept is attempted to minimize and maximize of the numerators and denominators from their respective ideal solutions and anti-ideal values simultaneously. Second, for each level, the K-dimensional objective space of each level is converted to a one-dimensional space by an aggregating function. Third, to obtain the final solution, all levels are combined into single-level model where the decision variables of upper levels are interrelated with other levels through fuzzy strategy-based linear and nonlinear membership functions.

The effectiveness of the proposed VIKOR is demonstrated by numerical examples, where the reported results affirm that the extended VIKOR method provides superior results in comparison with the same methods in the literature, and it is a good alternative to BL-MCNFP problems.

In terms of the assistance-based right decision, a parametric analysis for the weight of the majority is provided to exhibit a wide range of compromise solutions for the decision-maker.

In the last years, the use of free-online instructional videos has gained popularity among educators and students. Its success is mainly based on the provision of fast and inexpensive access to educational contents which can be consulted at the own convenience of students, all over the world. Free-online platforms as YouTube offer access to more than ten million instructional videos. The purpose of this paper is to assess and rank the educational quality of free-online instructional videos from a multidimensional perspective.

In this paper, the authors propose a MCDM approach based on a compromise ranking method, VIKOR. The approach integrates a normalization process which is especially suitable for situations where the nature of the different decision-making criteria is such that it does not allow homogeneous aggregation.

With the proposed normalization approach, the initial valuations of the alternatives with respect to the criteria are transformed in order to reflect their similarity with a given reference point (ideal solution). The normalized data are then integrated in a VIKOR-based framework in order to obtain those mathematical videos closer to the ideal video from the instructors’ perspective.

The ranking of instructional videos based on their quality from an educational multidimensional perspective is a good example of a real decision-making problem where the nature of the criteria, qualitative and quantitative, implies heterogeneous data. The proposed IS-VIKOR approach overcomes some of the problems inherent to this real decision-making problem.

An inherent problem on risk priority number (RPN) value duplication of traditional failure modes and effect analysis (FMEA) also exists in two customer-oriented FMEAs. One has no unique value, and another has 1% unique values out of 4,000 possible values. The RPN value duplication has motivated the development of a new customer-oriented FMEA presented in this paper to achieve practically all 4,000 unique values and delivering reliable prioritization.

The drastic improvement is the result of power-law and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). By having all three risk factors in a power-law form, all unique values can be obtained, and by applying VIKOR to these power-law terms, the prioritization is more practical and reliable.

The proposed VIKOR power law-based customer-oriented FMEA can achieve practically all 4,000 unique values and is tested with two case studies. The results are more logical than the results from the other two customer-oriented FMEAs.

The evaluation has been done on two case studies for the service sector. Therefore, additional case studies in other industrial sectors will be required to confirm the effectiveness of this new customer-oriented RPN calculation.

Achieving all 1,000 unique values could only be done by having experts tabulate all possible combinations for the traditional FMEA. Therefore, achieving all 4,000 unique values will be much more challenging. A customer-oriented FMEA has been developed to achieve practically all 4,000 unique risk priority numbers, and that the prioritization is more practical and reliable. Furthermore, it has a connection to the traditional FMEA, which helps explain the traditional one from a broader perspective.

This paper aims to presents a novel integrated fuzzy decision support system for analyzing the issues related to failure of a milk process plant unit.

Process failure mode effect analysis (PFMEA) approach was implemented to list failure causes under each subsystem/component and fuzzy ratings for three risk criteria, i.e. probability of failure occurrence (O_f), severity (S) and non-detection (O_d) are collected against the listed failure causes through experts feedback. A new doubly technique for order of preference by similarity to ideal solution (DTOPSIS) approach was implemented within fuzzy PFMEA tool for ranking of listed failure causes. The proposed decision support system overcomes the restrictions of classical PFMEA and IF-THEN rule base PFMEA approaches in an effective way.

Failure causes such as electrical winding failure (RM4), high pressure in plate region (C1), communication problem in supervisory control and data acquisition control (MS3), insulation problem (ST2), lever breakage (B2), gasket problem (D3), formation of holes (PHE5), cavitations (FP7), deposition of milk particle inside the pipeline because of improper cleaning (MHP2) were acknowledged as the most critical one with the application of proposed decision support system.

The analysis results are based on subjective judgments of the experts and therefore correctness of risk ranking results are totally dependent upon the quality of input data/information available from these experts. However, the analyst has taken proper care for considering the vagueness of the raw data by incorporating fuzzy set theory within the proposed decision support system.

The proposed fuzzy decision support system has been presented with its application on milk pasteurization plant of a milk process industry. The analysis based ranking results have been supplied to maintenance manager of the plant and a consent was shown by him with these results. Once the top management of the plant took decision for the implementation of these results, the detailed robustness of the proposed decision support system could be evaluated further.

The analysis result would be highly useful for minimizing sudden breakdowns and operational cost of the plant which directly contributes to plant's profitability. With the decrease in the chances of sudden breakdowns there would be high safety for the people working on/off the plant's site. Further, with increase in availability of the considered plant the societal daily demand related to dairy products could be easily fulfilled at reasonable prices.

The performance and proficiency of the proposed decision support system has been evaluated by comparing the ranking results with classical TOPSIS and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) approaches based results.

The “Internet of Things (IoT)” is a platform for involving smart devices via the Internet at a worldwide scale. It supports the “supply chain (SC)” and “information and communication technology (ICT)” infrastructure to be well integrated into an organization and externally with customers and suppliers. The “sustainable supply chain (SSC)” is currently unavoidable if a company seeks to satisfy the aggressive change in its customers' requirements. Numerous studies have confirmed that manufacturing firms have to accelerate the shift of their focus toward sustainability and the implementation of novel technologies, such as IoT, to accomplish their organizational goals most effectively. Although the literature consists of many theoretical approaches to IoT and numerous studies that have extremely concentrated upon the IoT technology and its potential applications, it lacks research with a focus on the challenges that arise when applying IoT to the “sustainable supply chain management (SSCM)”.

The present study proposes an integrated framework using the “Criteria Importance Through Intercriteria Correlation (CRITIC)” and “VlseKriterijumska optimizcija I kaompromisno resenje in Serbian (VIKOR)” models and employs to evaluate the IoT challenges to implement the SSCM. For estimating the criteria weights, the CRITIC tool is utilized. The organization's prioritization is obtained by the VIKOR procedure, which delivers simple mathematical procedures with precise and consistent outcomes.

To exhibit the practicality of the introduced model, a case study is taken to evaluate the IoT challenges to implement the SSCM within the “q-Rung Orthopair Fuzzy Sets (q-ROFSs)” environment. Moreover, the authors exhibit a sensitivity investigation over given parameter values, examining the stability of developed approach. Finally, the authors draw attention to a comparison between developed q-ROF-CRITIC-VIKOR decision-making approach with an existing q-ROF-TOPSIS method to show its superiority and potency.

The outcome of the study lies in observing the top benefits of individual businesses, and their entire SSCs can be found by implementing IoT. This paper investigates the most important challenges that individual firms and entire SSCs might while applying IoT. It provides a deep insight regarding the effects of IoT upon SSCM and the issues every firm need to contemplate when it is to apply IoT solutions.

To explore a hybrid approach in order to attain optimal cutting conditions proficient of generating adequate dimensional accuracy in combination with virtuous surface finish during turning of commercially pure titanium (CP-Ti) grade 2.

In the present paper, an application of the hybrid fuzzy–VIKOR method has been proposed to estimate an optimal combination of process variables during turning of commercially pure titanium (CP-Ti) grade 2. Three distinct input factors, namely, cutting speed, feed rate and depth of cut, were selected, each varied at three levels. Thus, a series of experiments were performed based on Taguchi's 3-factor-3-level (L₂₇) orthogonal array. The major attention was given to acquire minimum cutting force and flank wear along with good surface finish. The adequacy of the proposed methodology was verified with the help of ANOVA test.

The results of the investigation revealed that the suggested hybrid technique is quite effective, easily understandable and time-saving approach, which can be successfully implemented to solve various problems either of similar or of different kinds.

Increasing demand of qualitative as well as low cost products is identified as the main challenging task in the current competitive market. Therefore, estimation and selection of the most suitable machining environment are of paramount importance in a real-time manufacturing system. Machining process involves both qualitative and quantitative factors, may be conflicting in nature, all to be considered together. Consequently, an appropriate combination of the machining variables is evidently desirable to meet the aforesaid challenges effectively.

An appropriate system for analysing performance of supply chains is an important requirement for the effective utilization of the supply chains. The purpose of this paper is to develop a conceptual model for the task of analysing the performance of members of supply chains.

A thorough literature review of the methodologies proposed earlier by various authors has been made. In this paper a multi criteria decision-making (MCDM) framework comprising of two MCDM approaches is proposed for analysing performance of supply chain members.

Performance analysis of members of supply chain and the process of decision making based on the outcome of the analysis is a MCDM process. Since human judgements are often vague, the application of fuzzy concepts is appropriate for analysing the performance of supply chains. The framework proposed in this paper was validated in a company manufacturing textiles.

The methodologies proposed are of great use for large- and medium-sized enterprises. However, small organizations may not be able to allot enough resources to implement the methodologies proposed.

The framework developed can be applied for undertaking a comparative analysis of performance of members of supply chains. It can also be applied for the process of incorporation of new members into the supply chain.

Very few methods are available for analysing the performance of supply chains and the subject remains an under researched one. The major contribution of this paper is that it proposes a new framework.

The purpose of this paper is to make out a complete solution to logistic outsourcing problem in a medium‐scale organization by using consistent fuzzy preference relation (CFPR) and vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) method.

The initial approach to this research was to develop a comprehensive framework for logistic outsourcing problem and selection of most appropriate third party logistic (3PL) provider.

It has been found that the organization should outsource logistic activities. The alternatives (3PL providers) have also been ranked and the fifth 3PL provider has been termed as best third party logistic provider.

The parameters selected for this study and developed framework are applicable only to a medium‐scale organization manufacturing automobile parts in northern India.

This is probably the first time that an attempt has been made to apply the two‐phase methodology approach, using CFPR and VIKOR, to analyze a multi‐criteria logistic outsourcing problem. A case is provided which demonstrates how to solve logistic outsourcing, a multi‐criteria decision‐making problem.

Globalization in supply chain networks is urging manufacturing companies for the production of sustainable products with re-engineering technologies that offer competitive advantage in current market. However, the increasing sustainable illumes are influencing reverse logistics (RL) systems to analyze their impacts on economy, environment and society. Recently, China’s $62bn investment under the egis of China Pakistan Economic Corridor (CPEC), which comprises a number of infrastructure and energy projects is developing Pakistan as a part of “One Belt One Road” initiative. Accordingly, a substantial number of economical, ecological and social exercises will occur in closest future. The purpose of this paper is to investigate the impact of sustainable practices, i.e., environmental, economic and social sustainability on RL recovery options.

Sustainable concepts including environmental, economic and social and RL recovery options are extracted through extensive literature review. A number of researchers used a variety of methodologies for achieving their research objectives. However, the authors will be using a combination of VIsekriterijumska optimizacija i KOmpromisno Resenje (VIKOR) and grey relational analysis (GRA) technique under fuzzy environment in the case of CPEC.

Results show that waste management, impact on bio-diversity and economic growth are the most significant factors in designing sustainable RL recovery options. Moreover, remanufacture and reuse rank top among RL recovery options due their significant economic and environmental effects, whereas recycle and resell position last due to their high cost and cutting edge modern technologies.

Finally based on this model, it is possible for authorities to design a sustainable RL strategy for efficient operations in case of CPEC projects and other developing countries as well.

Negligible work has been done regarding sustainable modeling in RL strategies using a combination of VIKOR and GRA techniques subjected to fuzzy environment in the case of CPEC from perspective of developing country, i.e., Pakistan.

The purpose of this paper is to develop comprehensive criteria for evaluating fashion design schemes and used an integrated model which considers the interrelation between the clusters of evaluation and the influence between criteria for evaluating alternative fashion design schemes.

The integrated approach uses the advantages of all three methods: the Decision-Making Trial and Evaluation Laboratory (DEMATEL) can be used to analyse the interrelations between the major clusters of fashion design evaluation. The analytical network process can calculate the criterion weight that is adjusted based on the influence between different elements in the decision framework. The Visekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) determines the best fashion design by ranking a set of designs by using ten conflicting criteria.

Style is the decisive dimension because it is highly affected by other clusters. The comfort of the style is the most crucial criterion. “Veracious” is the best and most preferred design scheme.

The study develops the decisive cluster and criteria in designing a fashion design scheme. The proposed approach can be used as a decision analysis tool in fashion design and other fields and has various advantages (e.g. considering interrelations between clusters and influences between criteria, and ranking a set of alternatives), and therefore, is appropriate for practical circumstances.