MCDM Techniques Research Articles

Comparative analysis among doctors working in private and government hospitals in identifying and prioritizing essential stress factors during COVID-19- an AHP-TOPSIS approach

The spread of COVID-19 across the world, triggered multiple stresses among doctors working tirelessly round the clock to attend sick patients. Doctors had to cope with new environment thereby developing anxiety and fear. The current paper identifies and explores the stress intensity developed among doctors with the aid of multi-criteria decision analysis in doctors working in private and government hospitals of India during COVID-19. After identification of numerous stresses through questionnaire, weights are assigned to common most stress factors by employing AHP method. Furthermore, comparative analysis and prioritization of stress factors is performed with the aid of TOPSIS. The current combined system is a quantitative analysis furnished to establish the feasibility of the methods in weighing and MCDM in stress assessment. This study identifies and predicts the foremost stress factor which needs to be addressed by hospital management to keep doctors with a stable and fresh mindset. This research further establishes a proper MCDM technique which need to be applied in all hospital to regulate and distribute doctors work load without overloading them. Psychological stress is the foremost type of stress reported by multiple doctors. Results showed that lack of balance among personal and professional life followed by lack of communication is highly related problem in doctors in such adverse events.

Combining SWOT analysis and neutrosophic cognitive maps for multi-criteria decision making: a case study of organic agriculture in India.

The conventional agricultural system heavily depends on chemicals and inorganic fertilizers, which cause environmental issues. Organic agriculture impacts 6 of the 17 Sustainable Developmental Goals (SDGs) of the United Nations. Strategies to develop organic agriculture have used SWOT and MCDM techniques for analysis. However, the examination of the influence of one strategy over the other strategies has yet to be investigated. This paper proposes a model that combines the existing SWOT analysis with neutrosophic cognitive maps (NCM) models to analyze interconnections among the various strategies obtained from SWOT. This research deploys the proposed SWOT-NCM model to analyze the case study of developing organic farming in Tamil Nadu, India. It offers insights into the strategy's influence over other strategies so that the best is given maximum importance while implementing organic farming. The framework captures the interconnections and ranks the strategies by order of influence, providing fresh insights by taking the farmers' perspective while working with the strategies from the SWOT analysis to model an NCM. A comparative analysis of this SWOT-NCM model with other MCDM models that use SWOT to analyze the agriculture problem, and a sensitivity analysis of the proposed model, is performed. According to our study, the best possible strategy to encourage organic farming is minimum support price (MSP) and centralized procurement. This proposed model can analyze other MCDM problems that use SWOT analysis.

Evaluation of tool wears mechanism considering machining parameters and performance parameters for titanium alloy in turning operation on CNC

ABSTRACT Titanium alloys are frequently utilised in applications that call for high strength at high temperatures as well as excellent mechanical resistance. This alloy has excellent mechanical properties that enable improved performance from titanium alloys. In the current research, Taguchi L25 orthogonal array of experiments were conducted first, and MCDM techniques and ANNOVA were utilised to forecast the influencing machining factors. From MCDM three methods (SAW, VIKOR & TOPSIS) prediction algorithms which rank one for experiment no. 2. Experiment results shows that experiment no. 02 gives optimum/best results in terms of Tool life and surface roughness. While the process parameter has values cutting speed = 80 rpm, Feed rate = 018 rev/mm, Depth of cut = 0.12 mm, and Rake angle = 14 degrees. From ANOVA outcome for surface finish it is noticed that the process parameter rake angle is having Rank 01 for all levels. Thus rake angle is major influencing parameter to achieve a better quality of surface roughness. While in case of flank wear it is crystal clear that the process parameter DOC is having Rank 01 for all levels. Thus DOC is most influencing parameter to achieve lesser flank wear and better quality of tool life.

Implementing QSPR modeling via multiple linear regression analysis to operations research: a study toward nanotubes.

Chemical graph theory significantly predicts multifarious physio-chemical properties of complex and multidimensional compounds when investigated through topological descriptors and QSPR modeling. The targeted compounds are widely studied nanotubes attaining exquisite nanostructures due to their distinguishable properties attaining numeric values. The studied nanotubes are carbon, naphthalene, boron nitride, V-phenylene, and titania nanotubes. In this research work, these nanotubes are characterized through their significance level by implementing highly applicable MCDM techniques. TOPSIS, COPRAS, and VIKOR are used to perform a comparative analysis between them through each optimal ranking. The criteria originated from multiple linear regression modeling established between degree-based topological descriptors and the physio-chemical properties of each nanotube.

VlseKriterijumska Optimizacija I Kompromisno Resenj (VIKOR) Method: MCDM Approach for the Medical Diagnosis of Vector-Borne Diseases

In dealing with the medical decision making with uncertainty, clinical diagnosis of diseases is very difficult without the intervention of domain experts. In this work, an approach has been developed that provides hand held support to the medical practitioners for the medical diagnosis of diseases. With the assistance of the three domain experts of Delhi based Government hospital, linguistic information of four patients has been collected under IF environment. VIKOR method, a MCDM technique is utilized to rank the diseases among the patients. It seems that the conclusive outcomes of the investigation are same as diagnosed by medical specialists.

Integrated MCDM Approaches for Exploring the Ideal Therapeutic Plastic Disposal Technology: Probabilistic Hesitant Fuzzy Domain.

The probabilistic hesitant fuzzy set (PHFS) is a useful extended version of the hesitant fuzzy set (HFS), which allows decision-makers greater freedom in espousing their preferences through the use of hesitant evidence in the real DM method. As the implications for individuals and global concerns have grown, efficient clinical diagnosis of medical waste has been a major challenge, particularly in developing countries. Medical waste can be disposed of in a variety of ways. The essential thing is to decide which strategies work best. The optimal healthcare plastic waste disposal (HCPWD) option is a MCDM method involving a wide range of qualitative characteristics. The MCDM technique (ARAS) is then described, whereby the criterion weights are assessed using the recommended entropy weighted method (EWM) proportion and score function in order to increase the process utilisation. Moreover, the above-described approach is used to address a real-world problem by determining the optimal treatment option for healthcare waste (HCW) disposal. Finally, a feasibility analysis is given to support the stated viewpoint on HCPWD options being prioritised.

Dynamic load balancing upon the replication and deletion of cloud services

In the last decade, the considerable increase of the cloud services use has led to the need to have search and selection techniques that match both the requirements of end users and those of the system. Indeed, to select a cloud service that meet the needs of both system and user is a challenge, due to the several conflicting criteria problem for the user on one hand, and for the system, i.e., the load balancing between Virtual Machines (VMs), on the second hand. Therefore, the main challenge, in this context, is how to ensure the user requirements by maintaining the system performance constraint. To deal with this challenge, we present in this paper an approach based on the cloud service replication on one or more VMs when the number of the user requests will be important at a given moment. This allows better load balancing between VMs by distrusting the users’ requests over them. In addition, it allows to select the best cloud service according to the users need. However, the cloud services replication introduces the problem of the storage space saturation. Thus, our second contribution is to select and delete the cloud service replicas without degradation of the load balancing. The two proposed contributions are based on the MCDM techniques in order to select the VMs that can receive the replica of the cloud service and to select those, which their storage space is overloaded in order to delete the replica cloud service. The experimental results, based on Cloudsim simulator, show that our proposal can effectively achieve good performance (load balancing) and improve the response time.

Assessing the application of multi-criteria decision making techniques in hospitality and tourism research: a bibliometric study

PurposeMulti-criteria decision-making (MCDM) techniques are decision support systems that provide systematic approaches to solve hospitality and tourism (H&T) problems while minimizing the risk of failure. However, less is known about the application of MCDM techniques in H&T research. This study aims to systematically assess the use of MCDM techniques in H&T research to classify its current application and determine its application potential for H&T research.Design/methodology/approachThis study used bibliometric analysis to examine all published MCDM studies focused on H&T industries, since 1997. In addition, topic modelling was used to discover key concepts. Finally, top cited studies in terms of total citations per year and total citations were qualitatively reviewed for more insights.FindingsThe findings revealed an ongoing interest in applying MCDM techniques in H&T research. Specifically, the extension of fuzzy theory in MCDM techniques is burgeoning among H&T researchers. However, a certain number of MCDM techniques seem to be ignored in this field with a repetitive application of MCDM techniques in particular areas.Research limitations/implicationsThe data for the current research was solely retrieved from Scopus and other databases were not included. Therefore, future research is called for to re-examine the study by considering data from various databases.Originality/valueThis study contributes to extant H&T literature by identifying the most prolific and influential countries, journals, publications and trends by applying MCDM techniques in H&T research, and elucidating the implications and characteristics of MCDM techniques in H&T research.

An integrated QFD and fuzzy TOPSIS approach for supplier evaluation and selection

PurposeSupplier evaluation and selection is an essential (multi-criteria decision-making) MCDM process that considers qualitative and quantitative factors. This research work attempts to use a MCDM technique based on merging fuzzy Technique for Order Preference by Similarity to Ideal Solution (F-TOPSIS) and Quality Function Deployment (QFD) ideas. The study attempts to find the supplier's attributes (HOWs) to accomplish its goals after determining the product's characteristics to suit the company's needs (WHATs).Design/methodology/approachThe proposed research methodology comprises the following four steps: Step 1: Determine the product purchase requirements (“WHATs”) and those pertinent to supplier evaluation (“HOWs”). In Step 2, the relative importance of the “WHAT-HOW” correlation scores is determined and also the resulting weights of “HOWs”. In Step 3, linguistic evaluations of possible suppliers in comparison to subjective criteria are given to the decision-makers. Step 4 combines the QFD and F-TOPSIS techniques to select suppliers.FindingsA fuzzy MCDM method based on fusing and integrating fuzzy information and QFD is presented to solve the drawbacks of conventional decision-making strategies used in supplier selection. Using the F-TOPSIS method, fuzzy positive ideal solution (FPIS) and fuzzy negative ideal solution (FNIS), the relative closeness coefficient values for all alternatives are computed. The suppliers are ranked by relating the closeness of coefficient values. This method permits the combination of ambiguous and subjective data expressed as fuzzy-defined integers or linguistic variables.Originality/valueQFD and TOPSIS, two widely used approaches, are combined in this article to rank and evaluate suppliers based on the traits that the suppliers choose to prioritize. This study demonstrates that the method employed could address multiple-criteria decision-making scenarios in a computationally efficient manner. The effectiveness and applicability of the method are illustrated using an example.

Integrated Machine Learning Algorithms and MCDM Techniques in Optimal Ranking of Battery Electric Vehicles

The automobile industries across the world of this present age are streamlining the manufacture of battery electric vehicles (BEV) as a step towards creating pollution free environment. BEVs are used as an alternate strategy to alleviate the carbon emission at global level. As environmental conservation is one of the long standing sustainable 1f ?developmental goals it is the need of the hour to make a paradigm shift from fossil fuels to renewable energy sources, at the same time this also gives rise to a decision-making problem on making optimal choice of the electric vehicles. In this paper a decision making problem based on ten alternative BEVs and eleven criteria is considered from the earlier works of Faith Ecer. The new ranking method of multi-criteria decision making MCRAT(Multiple Criteria Ranking by Alternative Trace) is used together with three different criterion weight computing methods of AHP(Analytical Hierarchy Process) ,CRITIC (CRiteria Importance Through Intercriteria Correlation) & MEREC (MEthod based on the Removal Effects of Criteria). The results obtained are compared and validated using random forest machine learning algorithm. This research work conjoins multi-criteria decision making methods and machine learning algorithms to make optimal decisions on Battery electric vehicles and this integrated approach yields optimal ranking results and it will certainly create new rooms in decision-making approaches in coming days.

Integrated Multi-Criteria Decision Making Via Trapezoidal Neutrosophic Sets to Evaluate the Risks of Failure Mode

The purpose of a failure mode and effect analysis (FMEA) is to improve the safety and dependability of a system, product, procedure, or facility by identifying potential points of failure and determining the consequences of such failures. The assessment of failure modes, the weighting of risk factors, and the ranking of failure modes are all areas where the conventional FMEA falls short when put to use in the real world. To assess the hazard of failure modes in a trapezoidal neutrosophic sets environment, this research proposes a model that combines the neutrosophic sets and MCDM technique such as WASPAS. The WASPAS MCDM method is used to calculate the weights of standards and order the alternatives. Advantages of trapezoidal neutrosophic numbers in dealing with uncertainty, ambiguity, and incompleteness are combined with the benefits of WASPAS to create the suggested risk prioritization strategy.

Improvement of Lean Manufacturing approach based on MCDM techniques for sustainable manufacturing

Improvement of Lean Manufacturing approach based on MCDM techniques for sustainable manufacturing

Improvement of lean manufacturing approach based on MCDM techniques for sustainable manufacturing

Improvement of lean manufacturing approach based on MCDM techniques for sustainable manufacturing

Evaluation of flexible working styles with MCDM techniques within the scope of SWOT analysis

Evaluation of flexible working styles with MCDM techniques within the scope of SWOT analysis

Investigation of Smart City Components by AHP-BWM-FUCOM and DEMATEL Methods

The concept of smart city has emerged with the development of technology in the 21st century, based on the ideal city concept introduced in the 19th century. 
 Although over forty smart city components can be counted in the literature, the main six elements which are smart economy, smart people, smart governance, smart mobility, smart environment and smart living are mostly included in the studies.
 In this study, these six main smart city components is weighted by one of the most widely used MCDM techniques AHP, DEMATEL and more recently developed techniques BWM and FUCOM. The results of comparison is given at the end.

Novel Fermatean Fuzzy Bonferroni Mean aggregation operators for selecting optimal health care waste treatment technology

Fermatean fuzzy set (FFS) is an expedient tool in today’s world for coping with uncertainty, ambiguity, and incompleteness that emerge in many decision-making processes. In light of the relevance of FFS, this work offers a Multi-Criteria Group Decision Making (MCGDM) method together with Bonferroni mean and weighted Bonferroni mean operators in FF environment. These operators consider the interdependencies between the parameters into account during aggregation process in group decision making. On the other hand, health care waste (HCW) is an unavoidable byproduct of healthcare institutions, and so HCW management is vital owing to its negative influence on public health and environment. In this study, the proposed FFMCGDM has been applied to determine the optimal HCW treatment technologies (TT) for assuring sustainable environmental development, considering six TTs as alternatives assessing against nine criteria. Moreover, the proposed approach has been illustrated through an empirical case study of many district hospitals in Tripura, India. The obtained results are compared to other two well-known MCDM techniques as well as existing Fermatean Fuzzy Aggregation Operators (FFAOs). A sensitivity analysis has also been carried out to examine the stability of the model. From the analysis, it has been found that the proposed technique is competitive to obtain the optimal HCW TT. For further validation of the proposed method, a well-known MCDM problem, namely Green Supplier Selection (GSS) has been modeled and solved.

Evaluation of the route selection in international freight transportation by using the CODAS technique based on interval-valued Atanassov intuitionistic sets.

The selection of a proper international freight transport route is one of the crucial tasks for decision-makers since it can affect costs, efficiency, and transportation performance. Besides, the selection of suitable and appropriate freight routes can also reduce external costs of transportation such as emissions, noise, traffic congestions, accidents, and so on. Route selection in international transportation is a complicated decision-making problem as many conflicting factors and criteria affect the assessment process. It has been observed that there is no mathematical model and methodological frame used for solving these selection problems, and decision-makers make decisions on this issue based on their own experiences and verbal judgments in the research process. Therefore, a methodological frame is required to make rational, realistic, and optimal decisions on route selection. From this perspective, the current paper proposes using the IVAIF CODAS, an extended version of the traditional CODAS techniques, and using the Atanassov interval-valued intuitionistic fuzzy sets (IVAIFS) for processing better the existing uncertainties. The proposed model is applied to solve the route selection, a real-life decision-making problem encountered in international transportation between EU countries and Turkey. According to the results of the analysis, option A6 (i.e., Route-6 (Bursa-Istanbul-Pendik-Trieste (Ro-Ro)-Austria-Frankfurt/Germany) has been determined as the best alternative. These obtained results have been approved by a comprehensive sensitivity analysis performed by using different MCDM techniques based on interval-valued intuitionistic fuzzy sets. Hence, it can be accepted that the proposed model is an applicable, robust, and powerful mathematical tool; also, it can provide very reliable, accurate, and reasonable results. As a result, the proposed model can provide a more flexible and effective decision-making environment as well as it can provide valuable advantages to the logistics and transport companies for carrying out practical, productive, and lower cost logistics operations.

Understanding the behavior of Bancassurance service in India

This study is in developing India to develop policy recommendations for bancassurance markets Banking and Insurance in Europe Coordination of sub-sectors Discusses functional benefits. In the 1990s in European countries banking and When financial consolidation of insurance services began, most banks and insurance companies already do Some are listed for a period of time. Efficient frontier portfolio in European bancassurance markets and We study pairwise combinations. The current investigation in selecting alternatives in the supply chain Based on ratio analysis (MOORA). including multi-objective optimization Fuzzy MCDM technique is used. For selecting supply chain strategies MOORA Method is applied to three relevant numerical examples. In the operational research field, many MCDM methods have been developed in the previous period, highly specific and No extension yet. Therefore, in this paper, Perfect for solving many complex real-world problems an extended to propose the MOORA method, Space gray numbers and We integrate the MOORA method. The present study investigates a new technique called multi-objective optimization based on Ratio Analysis (MOORA) Faced with real-time manufacturing industries Solves a variety of multi-purpose problems. It's with many benchmarking issues Solves some unconventional machining processes. The alternative is Life insurance (MEAN SR), Life insurance (STD SR), Life Insurance (CV), Non-life insurance (MEAN SR), Non-life insurance (STD SR), Non-life insurance (CV), Insurance broker (MEAN SR), Insurance broker (STD SR), Insurance broker (CV). Evaluation parameter is insurance percentage, 0, 10, 25, 50, 75, 90, and 100. In this paper Bancassurance with insurance companies for Non-life insurance (CV) is got the first rank whereas is the Insurance broker (STD SR) is having the Lowest rank.

Sustainable Urban Conveyance Selection through MCGDM Using a New Ranking on Generalized Interval Type-2 Trapezoidal Fuzzy Number

This article proposes a modified ranking technique for generalized interval type-2 trapezoidal fuzzy numbers. For demonstrating uncertainty and managing imprecision in decision-making information, interval type-2 fuzzy sets are beneficial. The proposed ranking methodology resolves the difficulty of multi-criteria group decision-making on sustainable urban conveyance. Additionally, the proposed ranking approach considers all crucial aspects of transportation sustainability, including the effectiveness of durable transportation systems from economic, social, and ecological perspectives in multi-criteria group decision-making scenarios. The new ranking methodology yields superior outcomes for choosing sustainable urban transportation options. In the numerical part, studies compared the proposed ranking approach to other methods currently used for various MCDM techniques.

Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis

Optimization of Submerged Arc Welding Setting Parameters Using Taguchi-Based MCDM Techniques : A Comparative Analysis