Fuzzy Multiple Attribute Decision Research Articles

Intuitionistic Fuzzy Multiple Attribute Decision-Making Model Based on Weighted Induced Distance Measure and Its Application to Investment Selection

This paper investigates an intuitionistic fuzzy multiple attribute decision-making method based on weighted induced distance and its application to investment selection. Specifically, an intuitionistic fuzzy weighted induced ordered weighted averaging operator is proposed to eliminate the drawbacks of existing methods by extending the functions of the order-induced variables. The main advantage of the proposed operator is its dual roles of the order-inducing variables that can simultaneously induce arguments and moderate associated weights. A further extension of the proposed operator is its adaptation towards measuring intuitionistic fuzzy information more effectively. In addition, a multiple attribute decision-making model based on the proposed distance operators is proposed. Finally, the practicability and validity of the proposed model are illustrated by using a numerical example related to investment selection.

Application of Fuzzy Multiple Attribute Decision-Making for Selecting the Best Sustainable Orientation

Sustainability is an idea encompassed with various aspects still under exploration in addition to its vibrant and comprehensive nature. The Brundtland commission articulated that sustainable development is development that meets the needs of the present without compromising the ability of future generations to meet their own needs. A plunge for supporting the ideology of sustainability orientations with respect to manufacturing and their implementation are still in need, but the quantum of factors increases in the process of sustainability orientation selection during the implementation of sustainable manufacturing. Several undecided factors are intrinsic in the implementation of new sustainable manufacturing. Decision-making methods using probabilities to represent the three orientations such as alternate material change, manufacturing process change and design change of achieving sustainability cannot be used to prioritize them. Therefore, a fuzzy multiple attribute decision-making (FMADM) method was developed with a three-level hierarchical decision-making models based on the economic, environment and social aspects of sustainable development, to evaluate the three orientations involved in sustainable manufacturing. A case study was conducted in an Indian automotive component manufacturing organization with the FMADM model developed and the results effectively reflected the characteristics of the three orientations of sustainable manufacturing.

Coupling fuzzy multiple attribute decision-making with analytic hierarchy process to evaluate urban ecological security: A case study of Guangzhou, China

Urban ecosystem is plagued with complexities and uncertainties due to the interconnections among multiple subsystems, as well as human and environment interventions. In this study, a hybrid AHP-FMADM method through coupling fuzzy multiple attribute decision-making (FMADM) with analytic hierarchy process (AHP) is developed to evaluate urban ecological security (UES). AHP-FMADM has advantages in (i) reflecting interactive relationships among multiple attributes in UES, (ii) dealing with uncertainties expressed as imprecise linguistic terms and judgments, and (iii) achieving the ranking of alternatives based on pairwise comparison. Then, AHP-FMADM is applied to assessing the ecological security of Guangzhou from 2005 to 2015, where an urban ecological security evaluation indicator system is constructed based on the pressure–state–response conceptual model. A number of scenarios with different weight assignment modes are examined. Results indicate that the overall ecological security of the study city is gradually improved. Urban environment indicators contributes more to the ecological security level than social and economic indicators. However, although ecological security state and response level increase significantly, the ecological pressure has increased since 2012, which may result in a decline of ecological security. Compared to the traditional fuzzy synthetic analysis (FSA) approach with weighted sum operator, AHP-FMADM cannot only reduce the effect of the attributes with low importance and increase that with high importance, but also help decision makers determine alternative adaptation options and management schemes based on their preferences. These findings reveal that indicators with high importance degree need to be efficiently adjusted for decision makers to maintain ecological security, such as increase water reuse ratio and control the rapid growth of the population.

Improved hybridization of Fuzzy Analytic Hierarchy Process (FAHP) algorithm with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW)

In this research, the improvement of hybridization algorithm of Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) in selecting the best bank chief inspector based on several qualitative and quantitative criteria with various priorities. To improve the performance of the above research, FAHP algorithm hybridization with Fuzzy Multiple Attribute Decision Making - Simple Additive Weighting (FMADM-SAW) algorithm was adopted, which applied FAHP algorithm to the weighting process and SAW for the ranking process to determine the promotion of employee at a government institution. The result of improvement of the average value of Efficiency Rate (ER) is 85.24%, which means that this research has succeeded in improving the previous research that is equal to 77.82%. Keywords: Ranking and Selection, Fuzzy AHP, Fuzzy TOPSIS, FMADM-SAW.

A fuzzy hybrid integrated framework for portfolio optimization in private banking

Decision-making processes in private banking must comply with standards for risk management and transparency enforced by banking regulations. Therefore, investors must be supported throughout a risk-informed decision process. This paper contributes to the literature by presenting a hybrid integrated framework that considers personal features of the investor and additional characteristics imposed by regulations, for which linguistic evaluations are used with regard to risk exposure. The proposed approach for personal investment portfolios considers legal aspects and investor’s preferences as an input to the novel fuzzy multiple-attribute decision making approach for sorting problems proposed in this paper, called FTOPSIS-Class. Then, the next step of the proposed framework uses the sorting results for a fuzzy multi-objective optimization model that considers the risk and return associated with the investor’s profile over three objectives. The contributions of this paper are illustrated and validated by using a numerical application in line with a new trend for modern portfolio theory which enables a real world investor’s characteristics to be considered throughout the decision-making process.

Assessment of air quality in Haora River basin using fuzzy multiple-attribute decision making techniques

This paper deals with assessment of air quality in Haora River basin using two techniques. Initially, air quality indices were evaluated using a modified EPA method. The indices were also evaluated using a fuzzy comprehensive assessment (FCA) method. The results obtained from the fuzzy comprehensive assessment method were compared to that obtained from the modified EPA method. To illustrate the applicability of the methodology proposed herein, a case study has been presented. Air samples have been collected at 10 sampling sites located along Haora River. Six important air pollutants, namely, carbon monoxide, sulfur dioxide, nitrogen dioxide, suspended particulate matter (SPM), PM10, and lead, were monitored continuously, and air quality maps were generated on the GIS platform. Comparison of the methodologies has clearly highlighted superiority and robustness of the fuzzy comprehensive assessment method in determining air quality indices under study. It has effectively addressed the inherent uncertainties involved in the evaluation, modeling, and interpretation of sampling data, which was beyond the scope of the traditional weighted approaches employed otherwise. The FCA method is robust and prepares a credible platform of air quality evaluation and identification, in face of the uncertainties that remain eclipsed in the traditional approaches like the modified EPA method. The insights gained through the present study are believed to be of pivotal significance in guiding the development and implementation of effective environmental remedial action plans in the study area.

DECISION SUPPORT SYSTEM FOR DETERMINING SCHOLARSHIP RECIPIENTS USING TOPSIS FMADM METHOD

Granting scholarships to students aims to assist students in conducting lectures. Distribution of scholarships conducted by Muslim University Nusantara Al-Washliyah to help underprivileged or underachievers during their study The problem aims to choose some best alternative based on some attributes (criteria) used. In order to make decisions on fuzzy issues can be used Fuzzy Multiple AttributeDecision Making (FMADM). In this research modeling using Unified Modeling Language (UML) in FMADM with TOPSIS method and Weighted Product to select candidates of scholarship recipients.

Extension of the TODIM Method to Intuitionistic Linguistic Multiple Attribute Decision Making

Practical decision situations are becoming increasingly complicated. It is common for a person to select or rank alternatives with respect to multiple attributes, and the TODIM (an acronym in Portuguese of interactive and multiple attribute decision making) method, which is one of the first multiple attribute decision making (MADM) methods based on prospect theory, has received more attention due to its great performance in considering the bounded rationality of decision makers (DMs). However, the classical TODIM method can only handle the MADM problems with crisp numbers. In this paper, considering that intuitionistic linguistic variables are convenient to describe uncertain or imprecise information, we propose the intuitionistic linguistic TODIM (IL-TODIM) method and intuitionistic uncertain linguistic TODIM (IUL-TODIM) method to solve uncertain MADM problems with IL and IUL variables, respectively. Additionally, a novel distance measure for IUL numbers is developed, based on which we can obtain the corresponding dominance degree of one alternative over another. Finally, examples are provided to show the validity of the proposed methods, and we also conduct a comparison of the results between the IL-TODIM method and the existing intuitionistic fuzzy MADM methods to illustrate the effectiveness of our proposed methods.

Decision Support System For Election Of Members Unit Patients Pamong Praja

Civil Service Police Unit (municipal police) is part of the area in the enforcement of legislation and arrangements for public order and public tranquility . Decision Support System or DSS ( Decision Support System ) is a computer -based information systems whose main goal is to help decision -making utilize data and models to solve the problems that are unstructured and semi- structured . In accepting prospective members of the previous municipal police PSDM section sorting and selecting applicants one by one entering the data so that the data obtained is not clear didapt results of each participant. By using Fuzzy Multiple Attribute Decision Making (FMADM) is used to find an alternative from a number of alternatives to optimize certain criteria , while the Simple Additive Weighting method (SAW). SAW method is often also known term weighted summation method . The basic concept is to find a method SAW weighted summation of the performance ratings of all the attributes of each alternative.

Fuzzy multiple attribute decision access scheme in heterogeneous wireless network

A lot of researches focus on access selection schemes based on decision matrix in HWN (Heterogeneous Wireless Network). For the decision matrixes do not dynamically change with the constantly changing network, they do not resolve the contradiction between the algorithm complexity and terminal process capacity. In this paper, we propose an efficient access selection solution FMADA (Fuzzy Multiple Attribute Decision Access). Our main contribution is that we use some appropriate utility functions according to different characteristics of the decision-making factors and an adaptive filtering method, so as to forecast and formulate a dynamic decision matrix in HWN. Through the optimization, it improves the accuracy of normalizing network parameters, reduces the burden of terminate in process capability, and strengths the algorithm stability of access selection. In addition, the paper builds up a HWN access selection demonstration platform based on Mini2440 development board to verify the performance. The results show that it can reasonably and efficiently access the optimal network according to types of services, the user’s preference and actual network status.

Fuzzy Simple Additive Weighting Method in the Decision Making of Human Resource Recruitment

The Company is one of the jobs that was founded to reduce unemployment. The progress of a company is determined by the human resources that exist within the company. So, the selection of workers will join the company need to be selected first. The hardest thing in making a selection factor is the effort to eliminate the subjectivity of the personnel manager so that every choice made is objective based on the criteria expected by the company. To help determine who is accepted as an employee in the company, we need a method that can provide a valid decision. Therefore, we use Fuzzy Multiple Attribute Decision Making with Simple Additive Weighting method (SAW) to decide to make in human resource recruitment. This method was chosen because it can provide the best alternative from several alternatives. In this case, the alternative is that the applicants or candidates. This research was conducted by finding the weight values for each attribute. Then do the ranking process that determines the optimal alternative to the best applicants who qualify as employees of the company. Based on calculations by the SAW obtained the two highest ranking results are A5 (alternative 5) and A1 (alternative 1), to obtain two candidates received.

Development of an interval type-2 fuzzy sets based hierarchical MADM model by combining DEMATEL and TOPSIS

In this study, a new interval type-2 fuzzy multiple-attribute decision making model is developed by integrating Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Decision Making Trial and Evaluation Laboratory (DEMATEL). The proposed model utilizes hierarchical decomposition approach for reducing inherent complexity of the decision making problems. Additionally, interdependencies among problem attributes are taken into consideration by using interval type-2 fuzzy DEMATEL method. Finally, ranking orders of the alternatives are obtained by hierarchical interval type-2 fuzzy TOPSIS method. As there are several forms of interactions among criteria in real life settings, decision makers should be provided with the expert and intelligent systems which can overcome the preferential independence assumption. The proposed method is able to model causal dependencies by using interval type-2 trapezoidal fuzzy sets. The proposed method is implemented in a Strengths, Weaknesses, Opportunities, and Threats (SWOT)-based strategy selection problem.

New Interval-Valued Intuitionistic Fuzzy Behavioral MADM Method and Its Application in the Selection of Photovoltaic Cells

As one of the emerging renewable resources, the use of photovoltaic cells has become a promise for offering clean and plentiful energy. The selection of a best photovoltaic cell for a promoter plays a significant role in aspect of maximizing income, minimizing costs and conferring high maturity and reliability, which is a typical multiple attribute decision making (MADM) problem. Although many prominent MADM techniques have been developed, most of them are usually to select the optimal alternative under the hypothesis that the decision maker or expert is completely rational and the decision data are represented by crisp values. However, in the selecting processes of photovoltaic cells the decision maker is usually bounded rational and the ratings of alternatives are usually imprecise and vague. To address these kinds of complex and common issues, in this paper we develop a new interval-valued intuitionistic fuzzy behavioral MADM method. We employ interval-valued intuitionistic fuzzy numbers (IVIFNs) to express the imprecise ratings of alternatives; and we construct LINMAP-based nonlinear programming models to identify the reference points under IVIFNs contexts, which avoid the subjective randomness of selecting the reference points. Finally we develop a prospect theory-based ranking method to identify the optimal alternative, which takes fully into account the decision maker’s behavioral characteristics such as reference dependence, diminishing sensitivity and loss aversion in the decision making process.

Triangular Intuitionistic Fuzzy Multiple Attribute Decision Making and Their Applications to Risk Evaluation for Risk Investment Projects

In this paper, we investigate the multiple attribute decision making problems about risk evaluation for risk investment projects with triangular intuitionistic fuzzy information. Then, we proposed the triangular intuitionistic fuzzy Einstein weighted geometric (TIFEWG) operator, triangular intuitionistic fuzzy Einstein ordered weighted geometric (TIFEOWG) operator and triangular intuitionistic fuzzy Einstein hybrid geometric (TIFEHG) operator and we develop an approach to multiple attribute decision making with triangular intuitionistic fuzzy information. Finally, an illustrative example for evaluating the risk of the risk investment projects with triangular intuitionistic fuzzy information is given to verify the developed approach.

An Approach to Interval-Valued Intuitionistic Fuzzy Multiple Attribute Decision Making Based on the MSM Operator and Their Applications to Online Advertising Publisher Evaluation

The Maclaurin symmetric mean (MSM) was originally introduced by Maclaurin. The prominent characteristic of the MSM is that it can capture the interrelationship among the multi-input arguments. However, the researches on MSM are very rare, especially in fuzzy decision making. In this paper, we investigate the MSM operator and extend the MSM operator to interval-valued intuitionistic fuzzy environment and develop the interval-valued intuitionistic fuzzy Maclaurin symmetric mean (IVIFMSM) operator. Some desirable properties and special cases of IVIFMSM operator are discussed in detail. Based on IVIFMSM operator, an approach to multiple attribute decision making problems with interval-valued intuitionistic fuzzy information is developed. Finally, an illustrative example for online advertising publisher evaluation is given to verify the developed approach and to demonstrate its practicality and effectiveness.

Application of Fuzzy TOPSIS MADM approach in ranking & underlining the problems of plywood industry in India

AbstractThe manufacturing of plywood consists of simple procedural steps, but the range of problems associated with the plywood manufacturing industries, especially in the case of small-scale industries (SSI), is large. This paper describes the major problems faced by the plywood SSIs along with their cause and the ultimate effect, i.e. pruning the profits. Many cogent tools and techniques are present for the task, but an attempt has been made to apply multiple attribute decision-making (MADM) approach in ranking the problems in order of their extent on the basis of various parameters. Some suggestions for the improvement purposes have also been made to overcome the top-ranked problem. The study is the first of its type in a plywood industry, although same can be applied to other similar small-scale cluster industries like steel, textile, pharmaceutical, and automobile.

An Approach based on TOPSIS for Interval Type-2 Fuzzy Multiple Attributes Decision-making

An Approach based on TOPSIS for Interval Type-2 Fuzzy Multiple Attributes Decision-making

AN APPROACH FOR MADM PROBLEMS WITH INTERVAL-VALUED INTUITIONISTIC FUZZY SETS BASED ON NONLINEAR FUNCTIONS

This paper investigates an approach for multiple attribute decision making (MADM) problems with interval-valued intuitionistic fuzzy numbers (IVIFNs). To do that, the nonlinear score, accuracy and hesitation functions of IVIFNs are developed based on the normal distribution. The novelty of these nonlinear functions is that they have an additional variance value, which can have more information to rank IVIFNs than Xu and Chen’s score function and Ye’s accuracy function. Based on these nonlinear functions, a ranking method for IVIFNs is proposed. Furthermore, a nonlinearly optimized model is proposed to obtain attribute weights by integrating these nonlinear functions. Then, we develop an approach for interval-valued intuitionistic fuzzy MADM programs in which two cases are considered: the attribute weight information is known and particularly known. In the end, we apply the proposed approach to select green supplier.

Approaches to Interval Intuitionistic Trapezoidal Fuzzy Multiple Attribute Decision Making with Incomplete Weight Information

With respect to multiple attribute decision-making problems with interval intuitionistic trapezoidal fuzzy information, some operational laws of interval intuitionistic trapezoidal fuzzy numbers, score function, and accuracy function of interval intuitionistic trapezoidal fuzzy numbers are introduced. An optimization model based on the maximizing deviation method, by which the attribute weights can be determined, is established. For the special situations where the information about attribute weights is completely unknown, we establish another optimization model. By solving this model, we get a simple and exact formula, which can be used to determine the attribute weights. We utilize the interval intuitionistic trapezoidal fuzzy weighted averaging operator to aggregate the interval intuitionistic trapezoidal fuzzy information corresponding to each alternative, and then rank the alternatives and select the most desirable one(s) according to the score function and accuracy function. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment

Interval type-2 fuzzy set (IT2FS) offers interesting avenue to handle high order information and uncertainty in decision support system (DSS) when dealing with both extrinsic and intrinsic aspects of uncertainty. Recently, multiple attribute decision making (MADM) problems with interval type-2 fuzzy information have received increasing attentions both from researchers and practitioners. As a result, a number of interval type-2 fuzzy MADM methods have been developed. In this paper, we extend the VIKOR (VlseKriterijumska Optimizacijia I Kompromisno Resenje, in Serbian) method based on the prospect theory to accommodate interval type-2 fuzzy circumstances. First, we propose a new distance measure for IT2FS, which is comes as a sound alternative when being compared with the existing interval type-2 fuzzy distance measures. Then, a decision model integrating VIKOR method and prospect theory is proposed. A case study concerning a high-tech risk evaluation is provided to illustrate the applicability of the proposed method. In addition, a comparative analysis with interval type-2 fuzzy TOPSIS method is also presented.