MCDM Problems Research Articles

BW-TOPSIS: A Hybrid Method to Evaluate Software Testing Techniques

Software testing plays a significant role in various software development phases. There are so many software testing techniques available. Selecting the most suitable software testing technique based on multiple factors is challenging for software practitioners. This paper proposes an MCDM-based hybrid approach for selecting the most appropriate software testing technique among various available software testing techniques, considering multiple factors such as cost, schedule, resources, etc. Because of the involvement of multiple factors, the problem of selecting the most appropriate software testing technique can be modeled as an MCDM problem. This study proposes a hybrid approach by integrating two MCDM methods BWM (Best-Worst Method) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), for evaluating various software testing techniques considering multiple factors altogether. For the applicability of the proposed approach, an experimental study was conducted using seven software testing techniques and six evaluation criteria. Results show the proposed approach can be used as an efficient tool for selecting the most suitable software testing technique among various available testing techniques in the presence of multiple factors.

MCDM Problem using Generalized Dodecagonal Neutrosophic Number using Max – Min and Min – Max Principle

Deciding is the most vital part in any situation or problem that we face in our real time atmosphere. It is the situation where we must decide on the available choices. We have introduced Dodecagonal Neutrosophic Number and its properties. The concept of max-min and min-max principle is applied to the problem that is taken. The concept of heavy ordered weighted averaging operator by assigning equal weights to the attributes and a solution is found for a MCDM problem.

Using TODIM Approach with TOPSIS and Pythagorean Fuzzy Sets for MCDM Problems in the Bullwhip Effect

Using TODIM Approach with TOPSIS and Pythagorean Fuzzy Sets for MCDM Problems in the Bullwhip Effect

A Sensitivity Analysis on a MCDM Problem Evaluated by ARAS Method

Multi-Criteria Decision Making, also known as MCDM, is a highly helpful technique for assessing numerous issues and conclusions as well as resolving conflicts in daily life. The choice of any technique, service, or product is fraught with difficulties. The choosing of any useful product, such as a scooter, is an important task that requires careful research into the selection criteria, where MCDM techniques play a significant role. But the results that are coming with different MCDM methods are has to be consistent enough. This particular study associated with the checking or verifying the results that are evaluated by the Additive Ratio Assessment (ARAS) method with AHP weights for each Criterion.

Entropy based extended TOPOSIS method for MCDM problem with fuzzy credibility numbers

<abstract><p>Due to the vagueness and uncertainty of human cognition/judgments as related to complicated decision-making problems, existing fuzzy decision-making approaches merely signal fuzzy assessment values and lack degrees/levels of credibility for the fuzzy assessment values in alternatives over attributes. As a result, the fuzzy evaluative value's credibility degree highlights its significance and importance in the fuzzy decision-making problem. To improve the degrees/levels of credibility of fuzzy evaluation values, the fuzzy assessment values should be tightly linked to their credibility measures, which would result in more abundant and reliable assessment information. The major goal of this research was to describe new procedures for credible fuzzy numbers based on the Dombi t-norm and Dombi t-conorm. Dombi operations can benefit from the operational parameter's best tractability. These operations are more generalized for credibility fuzzy numbers. Furthermore, using the basic operational laws of Dombi t-norm and Dombi t-conorm, we develop a series of fuzzy credibility Dombi aggregation operators, like the fuzzy credibility Dombi geometric aggregation operator, fuzzy credibility Dombi ordered geometric aggregation operator and fuzzy credibility Dombi hybrid geometric aggregation operator. To handle this sort of decision-making problem, an extended TOPSIS (technique for order of preference by similarity to ideal solution) is proposed. Finally, we present an example, along with a discussion of the comparative results to check the accuracy and validation of the proposed methods, to confirm that their results are credible and feasible.</p></abstract>

Einstein Ordered Weighted Aggregation Operators for Pythagorean Fuzzy Hypersoft Set With Its Application to Solve MCDM Problem

The Pythagorean fuzzy hypersoft set is the most generalized form of the Pythagorean fuzzy soft set used to resolve indeterminate and inexplicit information in the decision-making procedure, considering the parameters’ multi-sub-attributes. Aggregation operators execute a dynamic role in considering the two prospect sequences and eliminating anxieties from this perception. The hybrid form of Pythagorean fuzzy sets with hypersoft sets has appeared as a supportive structure in fuzzy mathematics and ensued as a convenient perspective in decision-making. This paper prolongs the Einstein-weighted ordered aggregation operators for the Pythagorean fuzzy hypersoft set, which proficiently contracts with tentative and confusing data. Experts are using the Pythagorean fuzzy hypersoft set in their quest to report indefinite and specific decision-making processes. It is an effective technique for enlarging unsure facts in decision-making. Some operational laws for the Pythagorean fuzzy hypersoft set have been projected in light of Einstein’s operations. Two innovative Einstein-ordered aggregation operators were established based on operational laws: Pythagorean fuzzy hypersoft Einstein-ordered weighted average and Pythagorean fuzzy hypersoft Einstein-ordered weighted geometric operators with their essential properties. Multi-criteria decision-making is imperative in overcoming barriers to real-world complications. However, conventional methods of multi-criteria decision-making regularly provide inconsistent results. The extended model appraisals recognized score values to regulate robotic agri-farming equated to prevalent methods, which is more useful for agribusiness. A numerical illustration of decision-making complications in real-life farming is deliberated to authenticate the established method’s supremacy and applicability. Based on the anticipated aggregation operators, a robust multi-criteria decision-making method has been presented, which delivers the most appropriate outcomes compared to existing multi-criteria decision-making techniques. The consequences show that the intended approach is more effective and stable in handling rough information based on the Pythagorean fuzzy hypersoft set.

MCDM method on complex picture fuzzy soft environment

In this paper the concept of complex picture fuzzy soft set is defined. The MCDM problem considered consists of two methods. In the first method called CPFS CRITIC method complex picture fuzzy soft matrix is constructed. Normalized CPFS decision function is defined and using this function the normalized CPFS decision matrix is constructed and the weights of the parameters are determined. In the second method the weights of CPFS CRITIC method are taken to find CPFS decision matrix using selected parameters and their alternatives. The utility function depending on the beneficial and non-beneficial alternatives are defined and the integrated utility of each parameter is determined. This method is illustrated by taking four types of chillies as the alternatives and five nutrients as parameters and the best yielding variety of chilli is found. The proposed method is compared with CPFS-TOPSIS method. It is found that the best variety of chilli is the same in both the methods. However, the ranking of the other types of chilli differ.

Assessment of Hybrid Gene Selection Using the VIKOR Method

One of the crucial processes in the classification of microarray data is gene selection. Particle swarm optimization is gaining popularity as a powerful method for genetic selection since it uses fewer parameters and doesn't use complicated evolution operators. Some particle swarm optimization-based gene selection techniques may select non-optimal genes with a high probability because particle swarm optimization is likely to converge to local minima, which may result in premature convergence. It is still difficult to choose prognostic genes with low redundancy without excluding crucial genes.Research significance: Exposure to ionising radiation has been associated to leukaemia, and gene selection often involves two phases. All of the survivors of the World War II atomic bombings in Japan have been shown to have a significant incidence of leukaemia. Functional brain cancer imaging with positron emission tomography and magnetic resonance imaging is widely used to map regional changes in the brain function advanced over Last decade. Appreciating unique contribution of aerobics glycol sis new insights into the role of brain energy metabolism atropines signal transduction have emerged. Diagnoses of colon cancer in the United States the subject of this recommendation is colon cancer. In a different recommendation, rectal cancer is discussed. Smoking status is the most powerful predictor lung function Decrease in smokers with COPD. If you are a smoker advised older people are more likely to quit because they cannot stop smoking or their lungs are already damaged. Similarly, there is a nihilistic approach to that intervenes in smoking cessation. The incidence of Hodgkin's lymphoma, a rare form of cancer, rises in the third decade in women and subsequently drops, whereas in men it stays largely steady after this point. The presence of Hodgkin/Reed-Sternberg cells serves as the basis for the diagnosis of Hodgkin's lymphoma.VIKOR method used in multi-criteria analysis (MCDM). Although a popular method, mcdm problems there are some problems with solving. This study is traditional discussed the problems with VIKOR method. This intention of the take a look at is to resolve issues with the traditional VIKOR technique to keep away from numerical troubles in fixing is modified VIKOR approach to create. From the result it is seen that Leukemia is showing the highest value for SRBCT is showing the lowest value. Resulting in Leukemia ranked first, there SRBCT has low rank

Relations and compositions between interval-valued complex fuzzy sets and applications for analysis of customers’ online shopping preferences and behavior

Analyzing the relations and patterns that exist in complex data sets is an integral part of the research in complex fuzzy set theory. The main object of study in this paper is the interval-valued complex fuzzy set (IV-CFS) model. This adaptation of complex fuzzy sets can handle datasets with a time-periodic feature, and the partial ignorance that exists in the data as well as the process of assigning values for the membership functions, in addition to modeling multi-dimensional data. This paper focuses on finding the patterns and relations between complex data sets using the properties of interval-valued complex fuzzy sets (IV-CFSs). To achieve this objective, this paper establishes the concept of relations and the composition operation for IV-CFSs using the extensive properties of the Cartesian product. Some of the algebraic properties of the relations and compositions are also introduced to define the equivalence relation between IV-CFSs. The proposed method is then applied to an MCDM problem related to customers’ online shopping preferences and behavior. A detailed case study of this MCDM problem is then presented through the interpretation of the results that were obtained. A brief comparison is then presented between our proposed method and other methods in literature used to analyze patterns between complex data sets.

Banzhaf-Choquet-Copula-based aggregation operators for managing fractional orthotriple fuzzy information

The goal of the present research work is to develop a new family of aggregation operators (AOs) under the fractional orthotriple fuzzy (FOF) information and apply them to MCDM problems. At the start, the Archimedean coupla and co-coupla are extended to handle FOF information, and some operational law for fractional orthotriple fuzzy numbers (FOFNs) based on extended Archimedean copula (EAC) and extended Archimedean co-copula (EACC) is presented. The fractional orthotriple fuzzy Banzhaf Choquet-Copula aggregation operator and fractional orthotriple fuzzy Banzhaf Choquet-Copula geometric operators are defined based on the proposed operational laws of FOFNs. In addition, the modified maximum deviation approach and the Banzhaf function model are created to objectively determine the fuzzy measure (FM) of criteria sets. Finally, based on the defined AOs, the appropriate decision-making procedures are developed. The proposed approaches can effectively overcome the FMs of criteria sets that are subjectively assigned by decision makers, as well as some decision-making problems in which the weights of the criteria are incomplete (completely) unknown, and there is a correlation between all criteria set.

Developing Universally Applicable Service Quality Assessment Model Based on the Theory of Consumption Values, and Using Fuzzy Linguistic Preference Relations to Empirically Test Three Industries

Service quality is an important factor for a successful company. The SERVQUAL model is widely used. However, it has been controversial over the past 30 years. This research aims to develop a service quality measurement model that can be supported in conceptualization and universal applicability, and uses this model to identify the most important key factors of service quality for three industries. First, based on the theory of consumption values, this study used conceptualization and the modified Delphi method to develop a service quality assessment model—the consumption values-based service quality model (CV-SQ). The CV-SQ model was then used in conjunction with the fuzzy linguistic preference relations (Fuzzy LinPreRa) method to address MCDM problems. The findings suggested that the most important key factors of service quality comprised safety in the aviation companies, innovativeness in the travel agencies, and comfort in the hotels. The CV-SQ model can be supported by theoretical and empirical tests in conceptualization and universal applicability, and has made theoretical contributions to service quality management. The research results have provided practical contributions to the improvement of service quality in the three industries. What is more noteworthy is the weight of epistemic value ranked first and second among the three industries, but it had not been included in any service quality aspect classification schemes during the past three or four decades.

Specific character of objective methods for determining weights of criteria in MCDM problems: Entropy, CRITIC and SD

The comparative analysis of objective methods for determining the weights of criteria in the problems of multi-criteria decision-making is carried out. It is shown that the use of methods for determining the weights of criteria, based on formal processing of the decision matrix (Entropy, CRITIC, Standard deviation) for MCDM problems in some cases is not correct. It is demonstrated that the Entropy weighting method (EWM) is highly sensitive to evaluation of probabilities of states based on the decision matrix. For the Entropy method two modifications of estimation of probabilities of states are proposed that partially eliminate the contradictions of the basic EWM method. The first modification (EWM.df) is based on a statistical approach and it estimates the probabilities of states based on attribute distribution function. The second modification (EWM.dsp) estimates the probabilities of states based on the relative dispositions of attributes. Two options both have their supporting rationale. The analysis of integrated weighing methods is carried out and various options for aggregation of weights are given. An integrated EWM-Corr-method is proposed which allows to re-allocate the weights obtained by the Entropy method among correlated criteria.

Model for the Sustainable Material Selection by Applying Integrated Dempster-Shafer Evidence Theory and Additive Ratio Assessment (ARAS) Method

The construction industry is a vital part of the modern economic system. Construction work often has significant negative impacts on the environment and sustainable economic development, such as degradation of the environment, depletion of resources, and waste generation. Therefore, environmental concerns must be taken into account when evaluating and making decisions in the construction industry. In this regard, sustainable construction is considered as the best way to avoid resource depletion and address environmental concerns. Selection of sustainable building materials is an important strategy in sustainable construction that plays an important role in the design and construction phase of buildings. The assessment of experts is one of the most important steps in the material selection process, and their subjective judgment can lead to unpredictable uncertainty. The existing methods cannot effectively demonstrate and address uncertainty. This paper proposes an integrated Dempster-Shafer (DS) theory of evidence and the ARAS method for selecting sustainable materials under uncertainty. The Dempster-Shafer Evidence Theory is a relatively new and appropriate tool for substantiating decisions when information is nonspecific, ambiguous, or conflicting. The Additive Ratio Assessment (ARAS) method has many advantages to deal with MCDM problems with non-commensurable and even conflicting criteria and to obtain the priority of alternatives based on the utility function. The proposed method converts experts’ opinions into the basic probability assignments for real alternatives, which are suitable for DS evidence theory. It uses the ARAS method to obtain final estimation results. Finally, a real case study identifying the priority of using five possible alternative building materials demonstrates the usefulness of the proposed approach in addressing the challenges of sustainable construction. Four main criteria including economic, social, environmental, and technical criteria and 25 sub-criteria were considered for the selection of sustainable materials. The specific case study using the proposed method reveals that the weight of economic, socio-cultural, environmental, and technical criteria are equal to 0.327, 0.209, 0.241, and 0.221, respectively. Based on these results, economic and environmental criteria are determined as the most important criteria. The results of applying the proposed method reveal that aluminum siding with a final score of 0.538, clay brick with a score of 0.494, and stone façade with a final score of 0.482 are determined as the best alternatives in terms of sustainability.

A Comparative Analysis of Multi-Criteria Decision-Making Methods for Resource Selection in Mobile Crowd Computing

In mobile crowd computing (MCC), smart mobile devices (SMDs) are utilized as computing resources. To achieve satisfactory performance and quality of service, selecting the most suitable resources (SMDs) is crucial. The selection is generally made based on the computing capability of an SMD, which is defined by its various fixed and variable resource parameters. As the selection is made on different criteria of varying significance, the resource selection problem can be duly represented as an MCDM problem. However, for the real-time implementation of MCC and considering its dynamicity, the resource selection algorithm should be time-efficient. In this paper, we aim to find out a suitable MCDM method for resource selection in such a dynamic and time-constraint environment. For this, we present a comparative analysis of various MCDM methods under asymmetric conditions with varying selection criteria and alternative sets. Various datasets of different sizes are used for evaluation. We execute each program on a Windows-based laptop and also on an Android-based smartphone to assess average runtimes. Besides time complexity analysis, we perform sensitivity analysis and ranking order comparison to check the correctness, stability, and reliability of the rankings generated by each method.

On the use of data analysis and OR modelling in MCDM problems: a case analysis – a rejoinder to the paper by Sousa Ribeiro et al

Abstract Taking as an example the very interesting and motivating paper by Sousa Ribeiro et al. (2021) an attempt is made of providing a couple of insights into the decision making process from the point of view of the potentially helpful aspects of data analysis and OR-related modelling. These are just hints and suggestions, meant primarily to emphasise the multifaceted character of the decision making situations and processes, especially when concerning more complex issues. While the course of the procedure proposed and exemplified in Sousa Ribeiro et al. (2021) is treated as fully correctly and successfully carried out to the end, we wish to show the potential use of information, constituting in a sense a “by-product” of such a procedure, or, actually, of any similar procedure, aimed at supporting decision making.

Ordering of interval-valued Fermatean fuzzy sets and its applications

Fermatean fuzzy sets (FFSs) introduced by Senapati and Yager (2019) can handle the problems with imprecise and incomplete information more effectively than that of intuitionistic fuzzy sets introduced by Atanassov (1986). Senapati and Yager (2019) have established some basic Mathematical operations over the Fermatean fuzzy sets. They have also introduced the concept of score and accuracy function on the class of Fermatean fuzzy sets for comparing any two arbitrary FFSs. In this paper, firstly, we introduce the concept of interval-valued Fermatean fuzzy sets and establish some Mathematical operations on the class of IVFFSs. Secondly, we introduce various score functions in the class of IVFFSs and study their properties. Thirdly, we compare different ranking methods with the proposed score functions for showing the efficacy of the proposed score functions. Fourthly, we establish the interval-valued Fermatean fuzzy TOPSIS (IVFFTOPSIS) method for solving multi-criteria decision-making problems. Finally, we show the applicability of proposed score functions on IVFFSs and the IVFFTOPSIS method in solving MCDM problems using numerical examples.

AN APPROACH WEB SERVICE SELECTION BY QUALITY CRITERIA BASED ON SENSITIVITY ANALYSIS OF MCDM METHODS

Context. The problem of QoS based Web service from the list of Web services with equal or similar functionality was considered. This task is an essential part of the processes of finding, discover, matching and using Web services on the Internet due to the numerous offerings of Web services with equal or similar functionality. The reasonable selection of a suitable Web service takes into account a lot of user’s quality requirements, such as response time, throughput, reliability, cost, etc. Such a task is usually formulated as an MCDM problem, in which the parameters are the Web service quality factors and the importance degree of these factors. The object of this research is a process of selection Web services using MCDM methods, taking into accounts the user’s preferences and requirements to the Web service quality characteristics. The subject of the research is the LSP method, which, in addition to the degree of importance of the criteria used in all MCDM methods, simulates the user’s reasoning about quality, taking into account, in particular, such characteristics of the criteria as mandatory, sufficiency, desirability, simultaneity and substitutability. Objective. The objective of the work is to develop an approach for comparing the result of using the LSP method with the results of using other MCDM methods. Method. A method for calculating the weights of input criteria that are not always explicitly specified in the LSP method was proposed. For this, the conjunctive coefficients of impact are used, which are calculated as a result of the sensitivity analysis of the Web service generalized quality criterion to changes the partial quality criteria. This method underlies the proposed approach to comparing the efficiency of the LSP method with other MCDM methods, which consists of using the obtained weights as the weights of the input criteria for the MCDM methods. Results. The developed method and approach was verified experimentally. The Web service ranking produced by the LSP method was compared with the ones produced by SAW, AHP, TOPSIS and VIKOR methods. This comparison confirmed the efficiency of the proposed method and approach. Conclusions. From the obtained results of comparing the LSP method and the MCDM methods considered in this study, it follows that the proposed method and approach provide the equivalent input conditions for these methods as for the LSP method, which is a necessary condition for the correct comparison of MCDM methods. The use of the proposed approach made it possible to study the sensitivities of the considered MCDM methods. In practical applications, this approach can be used to select a suitable MCDM method. The proposed method can be useful for creating professional evaluation systems in which it is necessary to assess the importance (weights) of tens and hundreds of quality criteria.

Application of a Fuzzy MCDM Method to Select the Best Operating System for an Efficient Security-Aware Design of Embedded Systems

In this work, the authors present their solution to select the best operating system for an efficient security-aware design of embedded systems. This problem is formulated as a MCDM problem and solved using a hybrid approach combining fuzzy AHP and fuzzy VIKOR. This combination enables the authors to take profit of both methods. From AHP, they exploited the hierarchy and the pairwise comparison between criteria that leads to finding the importance (weight) of each criteria more consistently. On the other hand, from the VIKOR method, they leverage its power to compromise between conflictual criteria. Since they are dealing with unprecise and subjective advises, they opt for the fuzzy versions of the AHP and VIKOR methods dealing with triangular fuzzy numbers. They used fuzzy AHP to calculate weights of criteria which are served later as inputs for the fuzzy VIKOR method. The outcome of this work is to assist embedded designers to select the most appropriate embedded OS for efficient design of secure embedded systems.

Multi-Criteria Decision-Making Model using Intuitionistic Fuzzy Entropy and Variable Weight Theory

The aim of this research is to develop a new multi-criteria decision-making method that integrates an intuitionistic fuzzy entropy measure and variable weight theory to be implemented in different fields to provide a solution for MCDM problems when the available information is incomplete. A limited number of studies have considered determining decision maker’s weights by performing objective techniques, and almost all of these researches detected a constant weights for the decision makers. In addition, most of the MCDM studies were not formulated to perform sensitivity analysis. The new method is based on the TOPSIS model with an intuitionistic fuzzy entropy measure in the exponential-related function form and the engagement of the variable weight theory to determine weights for the decision-makers that vary as per attibutes. Lastly, a mathematical model was developed in this research to be as an input for developing the mobile-aplication based method in future for virtual use of the new MCDM method.

A new Pythagorean fuzzy-based decision-making method through entropy measure for fuel cell and hydrogen components supplier selection

While fuel cell combined with hydrogen (FCH) technology is still largely in its infancy striving to find its footing, the present market stage towards commercialisation is bridged by the pervasive research and development (R&D) and innovation. Providing spare parts and auxiliary components of the FCH systems plays a significant role in advancing the process. For the successful transition, an optimal supplier selection function can flourish the long-term research, and further, address the lack of technological knowledge to manufacture high performance and affordable components. This paper presents an integrated approach based on entropy, Step-wise Weight Assessment Ratio Analysis (SWARA) and Complex Proportional assessment (COPRAS) methods under the Pythagorean fuzzy environment for the FCH supplier selection. In this method, the criteria weights were first calculated by combining the objective weights determined by the entropy-based approach and the subjective weights by the SWARA method. For this purpose, a new entropy measure was proposed through the Pythagorean fuzzy set as one of the new flexible tools to handle the uncertain and inaccurate information arisen in complex MCDM problems. An integrated approach developed in this study can overcome the insufficiencies which arise either in an objective-weighting model or a subjective-weighting model. COPRAS was then utilised to evaluate the ranking order of the alternatives. A real-world case study of the FCH components supplier selection problem was considered to implement the proposed integrated approach. Finally, a comparison and sensitivity analysis were discussed to illustrate the usefulness of the proposed method.