Journal articles: 'Multi-criteria decision making technique'

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Jayady, Arman, Tonny Hidayat, Erni Qomariyah, et al. "Decision Support System with Multi Criteria Decision Making Technique." Journal of Physics: Conference Series 1933, no. 1 (2021): 012017. http://dx.doi.org/10.1088/1742-6596/1933/1/012017.

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Azhar, Nayli Adriana, Nurul Asyikin Mohamed Radzi, and Wan Siti Halimatul Munirah Wan Ahmad. "Multi-criteria Decision Making: A Systematic Review." (Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) 14, no. 8 (2021): 779–801. http://dx.doi.org/10.2174/2352096514666211029112443.

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Multi Criteria Decision Making (MCDM) helps decision makers (DMs) solve highly complex problems. Accordingly, MCDM has been widely used by DMs from various fields as an effective and reliable tool for solving various problems, such as in site and supplier selection, ranking and assessment. This work presents an in-depth survey of past and recent MCDM techniques cited in the literature. These techniques are mainly categorised into pairwise comparison, outranking and distance-based approaches. Some well-known MCDM methods include the Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), Elimination et Choix Traduisant la Realité (ELECTRE), Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). Each of these methods is unique and has been used in a vast field of interest to support DMs in solving complex problems. For a complete survey, discussions related to previous issues and challenges and the current implementation of MCDM are also presented.

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Elanchezhian, C., B. Vijaya Ramnath, and Dr R. Kesavan. "Vendor Evaluation Using Multi Criteria Decision Making Technique." International Journal of Computer Applications 5, no. 9 (2010): 4–9. http://dx.doi.org/10.5120/943-1321.

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Odu, G. O. "Weighting methods for multi-criteria decision making technique." Journal of Applied Sciences and Environmental Management 23, no. 8 (2019): 1449. http://dx.doi.org/10.4314/jasem.v23i8.7.

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Azadfallah, Mohammad. "Multi-Criteria Decision Making for Ranking Decision Making Units." International Journal of Productivity Management and Assessment Technologies 6, no. 1 (2018): 17–36. http://dx.doi.org/10.4018/ijpmat.2018010102.

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There is no doubt the Data Envelopment Analysis (DEA) is a powerful method for the efficiency evaluation of Decision Making Units (DMUs) with multiple inputs and outputs. Despite its usefulness, DEA has some notable limitations. A significant drawback with this approach is that inability to fully rank the DMUs. In the extant literature, different methods for this purpose have been suggested. While, in the traditional method the first step for the DEA approach is used, and results of this step are input for the DEA ranking method in the second step. To reduce the computational complexity of the traditional method, a new Multiple Criteria Decision Making (MCDM) approach is proposed in this article. In the proposed approaches, one step can achieve full ranking for all DMUs. The results show that although out of 20 DMUs are first in the final ranking ordered by the DEA, the author proposed methods can consider full ranking. Agreement of the proposed methods with the existing approaches are measured by the Spearman's rank correlation coefficient technique. The findings of this study reveal that TOPSIS, Neo-TOPSIS, and AHP ranking results are consistent with the DEA ranking method. Therefore, these proposed methods appear as the possible alternatives to the DEA and DEA ranking models.

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Badarovska Mishevska, Marina. "MULTI CRITERIA DECISION MAKING – RANKING AND PROMOTING EMPLOYEES." KNOWLEDGE INTERNATIONAL JOURNAL 31, no. 5 (2019): 1235–41. http://dx.doi.org/10.35120/kij31051235b.

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The analytic hierarchy process (AHP) is a structured technique for organizing and analyzing complex decisions, based on mathematics and psychology. The method was developed by Thomas L. Saaty in the 1970s and has been extensively studied and refined since then. It has particular application in group decision making and is used around the world in a wide variety of decision situation. Rather than prescribing a "correct" decision, the AHP helps decision makers choose one that best suits their goal and their understanding of the problem. The technique provides a comprehensive and rational framework for structuring a decision problem, for representing and quantifying its elements, for relating those elements to overall goals, and for evaluating alternative solutions. Decision making is the choice of one alternative, from two or more, to which the course of the activity is directed and the problem is solved. The decision-making process is a rational attempt by the manager to achieve the goals of the organizational unit. The decision-making process can be thought of as a "brain and nervous system" of an enterprise. Decisions are made when a person wants things to be different in the future. Given each specific situation, making the right decisions is probably one of the most difficult challenges for managers. Managers in day-to-day work deliver programmed and unprogrammed decisions that solve simple or complex problems. Simple decisions have an impact on the short-term performance of the enterprise, and complex decisions have an impact on the long-term future and success of the enterprise. Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to each other two at a time, with respect to their impact on an element above them in the hierarchy. The AHP converts these evaluations to numerical values that can be processed and compared over the entire range of the problem. In this article, it is explained the application of the AHP method in order to evaluate and promote employees in the enterprise "X" with several criteria. The obtained results enable the manager to evaluate the employees in an objective way and make an objective decision for their promotion. Its application for selecting the best among employees, in their assessment and promotion, allows managers to use a specific and mathematical tool to support the decision. This tool not only supports and qualifies decisions, it also allows managers to justify their choice, as well as to simulate possible results.

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PARIDA, P. K., S. K. SAHOO, and B. BEHERA. "Multi-criteria Decision Making Models using Fuzzy TOPSIS Technique." Journal of Ultra Scientist of Physical Sciences Section A 28, no. 5 (2016): 286–93. http://dx.doi.org/10.22147/jusps-a/280507.

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Selly Marselina Hutabarat. "Implementasi Metode Smart (Simple Multi Atribute Rating Technique) Dalam Menentukan Jurusan Di Sma Hkbp 2 Tarutung." Jurnal Multimedia dan Teknologi Informasi (Jatilima) 3, no. 02 (2022): 47–52. http://dx.doi.org/10.54209/jatilima.v3i02.149.

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Wrong One role of SPK in the field of education is in the decision-making process for the selection of majors in high school, which in nature can assist decision makers in providing alternative decisions for appropriate majors for students, where the results of the decisions can be used as material to assist teachers and students in making decisions. Most students only follow friends to follow friends to choose a major so that it allows students to feel unsuitable after entering the major. Therefore we need a decision support system that can calculate the value, ability and personality of students to help determine majors in high school. Smart is a multi-criteria decision-making method developed by Edward in 1977. This multi-criteria decision-making technique is based on the theory that each alternative consists of a number of criteria that have values and each criterion has a weight that describes how important it is compared to other criteria. The author uses this method to make it easier to determine the right major, according to the desired criteria. This problem can be classified into problems that are multi-objective (many goals to be achieved) and multi-criteria (many criteria that determine in reaching the decision). The author uses this method to make it easier to determine the right major, according to the desired criteria. This problem can be classified into problems that are multi-objective (many goals to be achieved) and multi-criteria (many criteria that determine in reaching the decision). The author uses this method to make it easier to determine the right major, according to the desired criteria. This problem can be classified into problems that are multi-objective (many goals to be achieved) and multi-criteria (many criteria that determine in reaching the decision).

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Alyazji, Qasem Anwar, and Gulsum Asiksoy. "Evaluating Mechanical Ventilators Using Multi Criteria Decision Making Techniques." International Journal of Online and Biomedical Engineering (iJOE) 17, no. 07 (2021): 4. http://dx.doi.org/10.3991/ijoe.v17i07.21769.

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Mechanical ventilator (MV) is used to help the patient breathe by delivering gas to the lungs at a certain rate using positive pressure. The complex evaluation of mechanical ventilator devices at present time is a very important and topical issue, due to the presence of many mechanical ventilator companies, as it seems that the process of evaluation and selection of ventilator equipment needs strong experience in this field. Our paper show that multi criteria decision making (MCDM) methods can be applied to comparing and evaluating some alternatives of mechanical ventilator devices. This study will determine new methodology to help the decision makers to choosing the best mechanical ventilator among the five alternatives based on eight criteria; Cost of the MV device; Maximum Inspiratory flow; Maximum Pressure; Tidal volume; PEEP; Weight of ventilator; Screen size and Internal battery time. This study used two techniques; TOPSIS technique and PROMETHEE II technique. Our paper used the same weights criteria in these two techniques. The weight for each criteria should be determined by the medical engineer expert and the decision makers. Choosing mechanical ventilator will affect the quality of the therapeutic and diagnostic processes, the way the treating doctor works, and also affect the patient's comfort. Because of these reasons, we designed a new methodology based on MCDM. This study will be an important basis for choosing the best mechanical ventilator, and will assist decision-makers such as medical engineers, ICU doctors, and users to evaluating and choosing the best ventilator based on several criteria.

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C., Gayatri, and S. M. "Study for Best Data Obfuscation Techniques using Multi-Criteria Decision-Making Technique." International Journal of Computer Applications 180, no. 43 (2018): 50–57. http://dx.doi.org/10.5120/ijca2018917137.

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Ozcalici, Mehmet. "Allocation with multi criteria decision making techniques." Decision Making: Applications in Management and Engineering 5, no. 2 (2022): 78–119. http://dx.doi.org/10.31181/dmame0305102022o.

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Saroja, S., T. Revathi, and Nitin Auluck. "Multi-Criteria Decision-Making for Heterogeneous Multiprocessor Scheduling." International Journal of Information Technology & Decision Making 17, no. 05 (2018): 1399–427. http://dx.doi.org/10.1142/s0219622018500311.

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This paper proposes a new tri-objective scheduling algorithm called Heterogeneous Reliability-Driven Energy-Efficient Duplication-based (HRDEED) algorithm for heterogeneous multiprocessors. The goal of the algorithm is to minimize the makespan (schedule length) and energy consumption, while maximizing the reliability of the generated schedule. Duplication has been employed in order to minimize the makespan. There is a strong interest among researchers to obtain high-performance schedules that consume less energy. To address this issue, the proposed algorithm incorporates energy consumption as an objective. Moreover, in order to deal with processor and link failures, a system reliability model is proposed. The three objectives, i.e., minimizing the makespan and energy, while maximizing the reliability, have been met by employing a method called Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). TOPSIS is a popular Multi-Criteria Decision-Making (MCDM) technique that has been employed to rank the generated Pareto optimal schedules. Simulation results demonstrate the capability of the proposed algorithm in generating short, energy-efficient and reliable schedules. Based on simulation results, we observe that HRDEED algorithm demonstrates an improvement in both the energy consumption and reliability, with a reduced makespan. Specifically, it has been shown that the energy consumption can be reduced by 5–47%, and reliability can be improved by 1–5% with a 1–3% increase in makespan.

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Tran Quang, Huy. "Optimizing University Student Housing Decisions: A MARCOS-Based Multi-Criteria Analysis." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 2 (2024): 165–67. http://dx.doi.org/10.62225/2583049x.2024.4.2.2457.

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Multi-criteria decision making (MCDM) techniques are crucial in decision-making situations with several conflicting criteria, helping to make well-informed and optimum decisions. This study utilizes the MARCOS technique, a well-known MCDM strategy, to help university students choose the optimal apartment leasing option nearby a Vietnamese institution. Data on two critical criteria, namely location distance to the university and monthly rental price, were collected from 18 apartment rental options. Through rigorous analysis utilizing the MARCOS method, the study identifies the most suitable apartment rental option for university students.

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Orakçı, Erhan, and Ali Özdemir. "Using Social Choice Function for Multi Criteria Decision Making Problems." Alphanumeric Journal 12, no. 1 (2024): 21–38. http://dx.doi.org/10.17093/alphanumeric.1426694.

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Many social choice preference functions or aggregation techniques, such as Borda, Copeland, Dodgson, Kemeny, are employed to obtain integrated solutions in multi-criteria decision problems. On the other hand, the number of studies comparing these techniques in the context of aggregation procedures in multi-criteria decision problems is limited. Furthermore, the advantages and disadvantages of the techniques have not been adequately discussed. In this context, the applicability of Borda, Copeland Dodgson, and Kemeny techniques in solving multi-criteria decision problems was investigated in this study. Analyses were performed on 500,000 samples containing various alternatives and sequences produced using the R software. The Kendall W test was used to assess the compatibility of the aggregation techniques. As a result, as the number of alternatives in the problem increases, the examined techniques produce an incomplete ranking. The features of the new aggregation technique to be developed were also determined in the context of the obtained results.

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Goyal, Anjali, and Neetu Sardana. "Optimizing bug report assignment using multi criteria decision making technique." Intelligent Decision Technologies 11, no. 3 (2017): 307–20. http://dx.doi.org/10.3233/idt-170297.

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Yang, Zhe, Kan Yang, Yufeng Wang, Lyuwen Su, and Hu Hu. "The improved multi-criteria decision-making model for multi-objective operation in a complex reservoir system." Journal of Hydroinformatics 21, no. 5 (2019): 851–74. http://dx.doi.org/10.2166/hydro.2019.150.

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Abstract In multi-objective reservoir operation, it is vital for decision-makers to select optimal scheduling schemes through efficient multi-criteria decision-making (MCDM) techniques. However, in the family of MCDM methods, it is difficult for the technique for order preference by similarity to an ideal solution (TOPSIS) to describe grey correlation, thus making decisions with less reliability. To this end, a framework supporting high-quality solutions' acquirement and optimal reservoir operation decision-making is established. The improved multi-objective particle swarm optimization (IMOPSO), a new efficient MCDM model based on TOPSIS and grey correlation analysis (GCA), and combination weighting method based on the minimum deviation (CWMMD) are included in the framework. The non-inferior solution set is efficiently obtained by IMOPSO and optimal decision information is provided for decision-makers using the MCDM model. Moreover, the CWMMD is used to determine weighting information of multiple evaluation indicators. Numerical simulations are conducted to verify the efficiency of the proposed methodology and support decision-making for multi-objective reservoir operation in Hongjiadu and Qingjiang basins. The results indicate that the proposed methodology can provide non-inferior scheduling solutions and decision-making instruction with higher reliability for multi-objective reservoir operation.

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Abdulaal, Reda M. S., and Omer A. Bafail. "Two New Approaches (RAMS-RATMI) in Multi-Criteria Decision-Making Tactics." Journal of Mathematics 2022 (September 27, 2022): 1–20. http://dx.doi.org/10.1155/2022/6725318.

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When a decision must be made, a tool called multi-criteria decision-making (MCDM) is used to assess and select alternatives among numerous criteria. For a wide variety of complex problems, MCDM methods have demonstrated usefulness in finding the optimal solutions. Despite the abundance of MCDM methods available today, there has been slow progress in developing new methodologies in MCDM in the past decade. In this context, this paper presents new MCDM tools which ranks alternatives based on median similarity (RAMS) between optimal alternatives and other alternatives. RAMS is an extension to the most recently developed technique that used perimeter similarity (RAPS). This paper also introduces a further tool that combines the RAMS method with the multiple criteria ranking by alternative trace (MCRAT) methodology using a majority index and the concept of the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. This tool is ranking the alternatives based on the trace to median index (RATMI). An illustration of the use of RAMS and RATMI is given through a case study of ranking different materials for the selection of break booster valve body in a vehicle. The validity of the new two techniques was tested against seven well-known MCDM techniques (ARAS, SAW, TOPSIS, COPRAS, VIKOR, WASPAS, and MOORA) using fifteen real problems data taken from the literature. The RATMI technique was more promising than RAPS and RAMS for 87% and 93% of the fifteen difficulties, respectively, according to the results of the correlation coefficient tests between the developed techniques and the selected seven techniques.

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Ranjan, Rajeev, Abhijit Saha, and Anil Kumar Das. "Comparison of Multi-Criteria Decision Making Methods for Multi Optimization of GTAC Process Parameters." Periodica Polytechnica Mechanical Engineering 66, no. 2 (2022): 166–74. http://dx.doi.org/10.3311/ppme.19835.

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A great deal of investigation on gas tungsten arc cladding (GTAC) is focused on the study of enhancements in the microstructure, mechanical and tribological features of the cladding. The selection of right process parameters is a critical issue for the researchers. Decision makers in the industries must analyze a wide variety of parameters based on a set of contradictory criteria. Several multi-criteria decision-making (MCDM) techniques are now available to add values in selection of these parameters. The application of the TOPSIS and MOORA techniques to identify the best configuration of processing parameters in the gas tungsten arc cladding (GTAC) process is investigated in this work. The best processing parameters set for the multiple performance attributes should be welding current: 70 amp, speed: 240, argon flow: 13 and standoff distance 3.5 (TOPSIS-PCA) and welding current: 50, speed: 300, argon flow: 13 and standoff distance 3.5 (MOORA-PCA).A comparison of MOORA-PCA and TOPSIS-PCA demonstrates the superiority of TOPSIS over MOORA technique. The prediction accuracy of the TOPSIS-PCA hybrid approach model is found better than MOORA-PCA technique.

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Sasirekha, V., C. Chandrasekar, and M. Ilangkumaran. "Heterogeneous wireless network vertical handoff decision using hybrid multi-criteria decision-making technique." International Journal of Computational Science and Engineering 10, no. 3 (2015): 263. http://dx.doi.org/10.1504/ijcse.2015.068835.

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Massam, Bryan H. "Multi-Criteria Decision Making (MCDM) techniques in planning." Progress in Planning 30 (January 1988): 1–84. http://dx.doi.org/10.1016/0305-9006(88)90012-8.

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Ranjithkumar, M. Arockia, J. Boobalan, L. Godlin Atlas, P. Sudhakar, and R. Senthil Kumar. "A interval valued intuitionistic fuzzy multi criteria decision making." E3S Web of Conferences 376 (2023): 01114. http://dx.doi.org/10.1051/e3sconf/202337601114.

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The limitations and disadvantages of the available intuitionistic fuzzy set scoring functions are investigated. Two improved methods for handling multi-criteria fuzzy decision-making problems are provided. They are based on the two theories of intuitionistic fuzzy set and cross entropy, with the adoption of cross entropy of the degree of membership from the degree of non-membership handling the effect of hesitancy degree. Score function method and weighted score function method are their names. This study presents and investigates a novel strategy for ranking interval-valued intuitionistic fuzzy sets. Examples using numbers are used to demonstrate the technique.

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Bray, Robert. "Developing a participative multi criteria decision making technique: a case study." International Journal of Management and Decision Making 14, no. 1 (2015): 66. http://dx.doi.org/10.1504/ijmdm.2015.067381.

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Ammarapala, Veeris, and James T. Luxhøj. "A Collaborative Multi‐criteria Decision Making Technique for Risk Factor Prioritization." Journal of Risk Research 10, no. 4 (2007): 465–85. http://dx.doi.org/10.1080/13669870701421563.

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Harahap, Muhammad Ade Kurnia, Ira Modifa Tarigan, Kraugusteeliana Kraugusteeliana, Sanco Simanullang, Ernie C. Avila, and Robbi Rahim. "A Multi-Criteria Analysis of University Housing Options using Weighted Sum Model." JINAV: Journal of Information and Visualization 4, no. 1 (2023): 93–98. http://dx.doi.org/10.35877/454ri.jinav1697.

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This study presents a novel application of the Multi-Criteria Decision-Making (MCDM) Weighted Sum Model (WSM) technique to assist students in selecting suitable university housing options. We identified five key criteria—location, affordability, amenities, room type, and social environment—based on a survey of prospective students' preferences. Using the Analytic Hierarchy Process (AHP), we calculated the weights for each criterion, reflecting the priorities of the surveyed students. We then applied the MCDM-WSM methodology to rank the housing options by calculating the weighted scores for each criterion. Our findings reveal a ranked list of university housing options that can guide students in making well-informed decisions based on their needs and preferences. The study demonstrates the significance of using advanced decision-making techniques in transforming complex decision-making processes into more structured, transparent, and reliable approaches. Furthermore, it highlights potential research gaps and future research directions to enhance the quality of choices and cater to the diverse needs of students in selecting university housing.

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Mateen, Muhammad Haris, Ibrahim Al-Dayel, and Turki Alsuraiheed. "Fermatean Fuzzy Fairly Aggregation Operators with Multi-Criteria Decision-Making." Axioms 12, no. 9 (2023): 865. http://dx.doi.org/10.3390/axioms12090865.

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A Fermatean fuzzy set (FRFS) is the extension of a fuzzy set, an intuitionistic fuzzy set, and a Pythagorean fuzzy set, and is used in different fields. Unlike other fuzzy structures, the sum of cubes of membership grades in FRFSs approximates a unit interval, increasing uncertainty. In this study, we intend to provide unique operational rules and aggregation operators (AOs) inside a Fermatean fuzzy environment. To develop a fair remedy for the membership degree and non-membership degree features of “Fermatean fuzzy numbers (FRFNs)”, our solution introduces new neutral or fair operating principles, which include the concept of proportional distribution. Based on the suggested operating principles, we provide the “Fermatean fuzzy fairly weighted average operator and the Fermatean fuzzy fairly ordered weighted averaging operator”. Our suggested AOs provide more generalized, reliable, and exact data than previous techniques. Combining the recommended AOs with multiple decision-makers and partial weight information under FRFSs, we also devised a technique for “multi-criteria decision-making”. To illustrate the application of our novel method, we provide an example of the algorithm’s effectiveness in addressing decision-making challenges.

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Kesireddy, Adarsh, and F. Antonio Medrano. "Elite Multi-Criteria Decision Making—Pareto Front Optimization in Multi-Objective Optimization." Algorithms 17, no. 5 (2024): 206. http://dx.doi.org/10.3390/a17050206.

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Optimization is a process of minimizing or maximizing a given objective function under specified constraints. In multi-objective optimization (MOO), multiple conflicting functions are optimized within defined criteria. Numerous MOO techniques have been developed utilizing various meta-heuristic methods such as Evolutionary Algorithms (EAs), Genetic Algorithms (GAs), and other biologically inspired processes. In a cooperative environment, a Pareto front is generated, and an MOO technique is applied to solve for the solution set. On other hand, Multi-Criteria Decision Making (MCDM) is often used to select a single best solution from a set of provided solution candidates. The Multi-Criteria Decision Making–Pareto Front (M-PF) optimizer combines both of these techniques to find a quality set of heuristic solutions. This paper provides an improved version of the M-PF optimizer, which is called the elite Multi-Criteria Decision Making–Pareto Front (eMPF) optimizer. The eMPF method uses an evolutionary algorithm for the meta-heuristic process and then generates a Pareto front and applies MCDM to the Pareto front to rank the solutions in the set. The main objective of the new optimizer is to exploit the Pareto front while also exploring the solution area. The performance of the developed method is tested against M-PF, Non-Dominated Sorting Genetic Algorithm-II (NSGA-II), and Non-Dominated Sorting Genetic Algorithm-III (NSGA-III). The test results demonstrate the performance of the new eMPF optimizer over M-PF, NSGA-II, and NSGA-III. eMPF was not only able to exploit the search domain but also was able to find better heuristic solutions for most of the test functions used.

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Ansyah, Raji, Grzegorz Filcek, and David M. Ramsey. "EVALUATING A COMPUTER APPLICATION THAT AIDS MULTI-CRITERIA DECISION MAKING." Multiple Criteria Decision Making 18 (2023): 47–76. http://dx.doi.org/10.22367/mcdm.2023.18.03.

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In this article, we describe and assess the implementation of several methods of multi-criteria decision-making using a web-based computer application. Such an application makes it easier to determine the effective- ness of decisions. The methods adopted in this application are SMART (Simple Multi-Attribute Rating Technique), AHP (Analytic Hierarchy Pro- cess), and ANP (Analytic Network Process). Each of these methods has distinctive characteristics in determining the best alternative for the user. This study assesses the feasibility of each method in the application. The application is assessed based on functionality, reliability, efficiency, and usability. (1) Functionality is tested according to the appropriateness of the decisions made, (2) Reliability is assessed using stress testing, (3) Effi- ciency is assessed according to the computational effort, and (4) System usability is tested according to the user’s answers to the Computer System Usability Questionnaire authored by J.R. Lewis. This research results in a decision support system based on SMART that has been appropriately tested and is ready for use. Keywords: multi-criteria analysis, SMART, AHP, ANP, system usability.

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Gardashova, Latafat, and Alish Nazarov. "Development of a decision support system using advanced multi-criteria decision-making techniques." Technology audit and production reserves 1, no. 2(81) (2025): 62–68. https://doi.org/10.15587/2706-5448.2025.323377.

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The object of research is decision-making processes in conditions of uncertainty, with an emphasis on improving the accuracy and reliability of multi-criteria decision-making methods. The problem to be solved is the difficulty of making reliable and optimal decisions in dynamic environments where data variability, incomplete information, and subjective judgments pose significant challenges. Traditional methods often fail to adequately address these complexities, leading to suboptimal or unreliable outcomes. The essence of the results lies in the creation of a DSS (Decision Support System) that leverages Z-number TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) to combine performance metrics with confidence levels, providing a more comprehensive framework for decision-making. The system is uniquely suited to prioritize alternatives effectively, even when faced with high levels of uncertainty and variability in input data. Due to its features and characteristics, the DSS allows for greater adaptability and precision in decision-making, ensuring results that are not only accurate but also reliable. The explanation for these results lies in Z-number TOPSIS’s ability to integrate quantitative analysis with the evaluation of data reliability, making it far more effective than traditional MCDM (Multi Criteria Decision Making) techniques. A systematic comparison with other methods, such as traditional TOPSIS and Fuzzy TOPSIS, demonstrates that Z-number TOPSIS consistently outperforms these approaches, particularly in scenarios involving dynamic and uncertain conditions. The study contributes to the advancement of decision-making methodologies by providing insights into how uncertainty can be systematically incorporated into ranking models. A comparative analysis with traditional TOPSIS and Fuzzy TOPSIS shows that Z-number TOPSIS outperforms these methods, providing a 10 % improvement in consistency under noisy data conditions and a 15 % better adaptability under conflicting criteria scenarios. The results are applicable in fields such as supply chain management, where decision-makers must optimize inventory distribution and supplier selection under fluctuating demand, healthcare, where prioritization of patient treatment is required under resource constraints, and financial risk assessment, where investment decisions depend on uncertain economic conditions. The findings highlight the potential of Z-number TOPSIS in supporting more reliable and adaptable decision-making processes in complex and uncertain environments.

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García, Vicente, J. Salvador Sánchez, and Ana I. Marqués. "Synergetic Application of Multi-Criteria Decision-Making Models to Credit Granting Decision Problems." Applied Sciences 9, no. 23 (2019): 5052. http://dx.doi.org/10.3390/app9235052.

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Although various algorithms have widely been studied for bankruptcy and credit risk prediction, conclusions regarding the best performing method are divergent when using different performance assessment metrics. As a solution to this problem, the present paper suggests the employment of two well-known multiple-criteria decision-making (MCDM) techniques by integrating their preference scores, which can constitute a valuable tool for decision-makers and analysts to choose the prediction model(s) more properly. Thus, selection of the most suitable algorithm will be designed as an MCDM problem that consists of a finite number of performance metrics (criteria) and a finite number of classifiers (alternatives). An experimental study will be performed to provide a more comprehensive assessment regarding the behavior of ten classifiers over credit data evaluated with seven different measures, whereas the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization METHod for Enrichment of Evaluations (PROMETHEE) techniques will be applied to rank the classifiers. The results demonstrate that evaluating the performance with a unique measure may lead to wrong conclusions, while the MCDM methods may give rise to a more consistent analysis. Furthermore, the use of MCDM methods allows the analysts to weight the significance of each performance metric based on the intrinsic characteristics of a given credit granting decision problem.

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Arora, H. D., and Anjali Naithani. "Multi-Criteria Decision Making to Logarithmic Pythagorean Fuzzy Entropy Measure Under TOPSIS Approach." International Journal of Fuzzy System Applications 11, no. 4 (2022): 1–23. http://dx.doi.org/10.4018/ijfsa.312237.

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One of the most essential ideas for tracing the best objects among a set of possible ones is decision-making theory. We make decisions to gain a wide range of advantages from them based on our previous experiences. The concept of Pythagorean fuzzy sets (PFS) was first established by Yager to provides a new technique to describe ambiguity with great precision when compared to intuitionistic fuzzy sets (IFS) and fuzzy sets (FS). The study of PFS is recently gaining importance due to its wide application in situations involving ambiguity. It can easily be merged with MADM techniques to solve real-life problems. However, many of these measures for PFS are ineffective in the sense that they have fundamental shortcomings that restrict them from providing reliable and consistent results. This paper provides a novel Pythagorean fuzzy entropy measure and its application to decision-making problem using technique for order preference by similarity of ideal solution (TOPSIS) on some real-life environment. Comparative study is also done for validation of the proposed measure.

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R. Ramesh. "Application of Neutrosophic Sets in Multi Attribute Decision Making." Communications on Applied Nonlinear Analysis 32, no. 9s (2025): 2635–49. https://doi.org/10.52783/cana.v32.4545.

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The selection of an optimal hospital for healthcare services is a complex decision-making problem due to the involvement of multiple, often conflicting, criteria such as quality of care, infrastructure, staff expertise, cost, and patient satisfaction. This paper presents an innovative approach for hospital selection using a hybrid decision-making framework combining neutrosophic sets, entropy weight, and the Multi-Attribute Decision-Making (MADM) method. Neutrosophic sets are employed to handle the inherent uncertainty and indeterminacy in hospital evaluation criteria, allowing for more flexible and accurate representation of data that may not be fully precise or certain. The entropy weight method is applied to objectively determine the significance of each evaluation criterion, ensuring that the decision process is not biased by subjective judgments. Finally, the MADM technique integrates the weighted criteria into a comprehensive decision model to rank hospitals based on their overall performance. The proposed model is tested with a real-world dataset of hospitals, demonstrating its effectiveness in selecting the most suitable healthcare facility while considering diverse factors. The results highlight the potential of combining neutrosophic sets with advanced decision-making techniques for improving decision accuracy and reliability in complex healthcare decisions.

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Modiri, Mahmoud, and Mohammad Dashti. "Strategic Decision Making for Outsourcing Information Systems with a Fuzzy Multi-criteria Decision-Making Approach." International Journal of Emerging Research in Management and Technology 6, no. 8 (2018): 6. http://dx.doi.org/10.23956/ijermt.v6i8.112.

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Today, IS supplier selection is one of the most critical steps in the outsourcing process; the success of outsourcing is highly dependent on the selection of IS suppliers. This paper proposes a new hybrid fuzzy multi-criteria decision-making (MCDM) model, which uses decision-making trial and evaluation laboratory (DEMATEL) technique, analytic network process (ANP), and Vlse Kriterijumska Optimizacija I Kompromisno Resenje(VIKOR) to evaluate four potential suppliers using seven factors and five decision makers using a realistic case study. the results showed that Service support is importance for outsourcing. The proposed model can help practitioners improve their decision making process.

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Lukianenko, L., and I. Goncharenko. "COMBINED STOCHASTIC TECHNIQUE. COMPARISON OF RESULTS OBTAINED BY DIFFERENT MULTI CRITERIA DECISION MAKING TECHNIQUES." Tekhnichna Elektrodynamika 2019, no. 1 (2019): 55–62. http://dx.doi.org/10.15407/techned2019.01.055.

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Wu, Wenshuai, Gang Kou, and Yi Peng. "Group decision-making using improved multi-criteria decision making methods for credit risk analysis." Filomat 30, no. 15 (2016): 4135–50. http://dx.doi.org/10.2298/fil1615135w.

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Credit risk analysis is a core research issue in the field of financial risk management. This paper first investigates the analytic hierarchy process (AHP) as a method of measuring index weights for group decision-making (GDM). AHP for group decision-making (AHP-GDM) is then researched and applied, taking into full account the cognitive levels of different experts. Second, the concept of grey relational degree is introduced into the ideal solution of the technique for order of preference by similarity to ideal solution (TOPSIS). This concept fully considers the relative closeness of grey relational degree between alternatives and the ?ideal? solution in order to strengthen their relationship. The AHP-GDM method overcomes the problem of subjectivity in measuring index weights, and the revised TOPSIS (R-TOPSIS) method heightens the effectiveness of assessment results. An illustrative case using data from Chinese listed commercial banks shows that the R-TOPSIS method is more effective than both TOPSIS and grey relational analysis (GRA) in credit risk evaluation. The two improved multi-criteria decision making (MCDM) methods are also applied to empirical research regarding the credit risk analysis of Chinese urban commercial banks. The results indicate the validity and effectiveness of both methods.

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Risawandi and Rahim Robbi. "Study of the Simple Multi-Attribute Rating Technique For Decision Support." International Journal of Scientific Research in Science and Technology (IJSRST) 2, no. 6 (2017): 491–94. https://doi.org/10.5281/zenodo.239697.

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Making a decision is a crucial step in a management, the decision will have a significant impact on the policies to be taken by the top management, SMART (Simple Multi-Attribute Rating Technique) is the method used for making a decision with the completion of many criteria with results pretty good, this study provides an overview of how the methods SMART (Simple Multi-Attribute Rating Technique) works with many criteria.

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LASTRA, O. ESPINOZA, L. Baque Villanueva, and A. Izquierdo Mor� Morán. "Neutrosophic Multi-Criteria Method for Selecting Optimum Market." International Journal of Neutrosophic Science 19, no. 1 (2022): 298–305. http://dx.doi.org/10.54216/ijns.190126.

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The Indonesian rolling stock maker's target market and business strategy are analyzed here—the study's planning, data, and technique. To achieve sustainable growth across the board in the power generating industry, we concentrate on understanding the critical variables driving sustainable development in a market context unlike before. To identify the most vital aspects to consider while dealing with ambiguous rules, a methodology using Multiple-Criteria Decision-Making (MCDM) was presented. To address ambiguity and bring the problem-solving process closer to reality, we created a unique method that integrates MCDM techniques. Analytical Hierarchy Process AHP was employed in this investigation. To zero in on our ideal clientele, we turned to the AHP technique. This strategy considers quantitative aspects such as market characteristics and degree of competition when making decisions. The results indicate that rolling stock manufacturers have good reason to invest in expanding their share of these markets. However, despite the many prospects available in this field, the rolling stock producer faces a significant obstacle: the inability to adequately fund the pursuit of a more considerable portion of the market

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Noaman, Abdulrahman A., Omer A. Bafail, Reda M. Abdulaal, and Mohammed H. Alamoudi. "Evaluation Of University Research Centers Performance Using Combined Multi-Criteria Decision-Making Model." International Journal of Advanced Engineering Research and Applications 8, no. 01 (2022): 11–26. http://dx.doi.org/10.46593/ijaera.2022.v08i01.002.

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Multi-Criteria Decision-Making (MCDM) focuses on reaching the best possible results in complex scenarios with conflicting criteria. The goal of this paper is to evaluate and rank the 26 research centres’ outputs at a large public university using some MCDM techniques. While the current method of evaluating and ranking research centers in that university is based on weighting processes developed by a group of University experts, this paper incorporates Analytic Hierarchy Process (AHP), Stepwise Weight Assessment Ratio Analysis (SWARA), and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) among other MCDM techniques. The AHP was utilized to check for consistency across expert-determined criteria importance, followed by SWARA which was used to find the relative criteria weights. The TOPSIS methodology was then applied to rank research centers at that University as “alternatives”. The Spearman’s correlation coefficient between the present rank and the suggested rank from the integrated AHP-SWARA-TOPSIS model was calculated. Based on the obtained correlation coefficients from Spearman’s technique, it is encouraging to use the proposed model as the number of centers increases.

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Deshmukh, GD, and Dr Rajendra Gupta. "Faculty Performance Analysis by Implementing Optimization Technique on Multi Criteria Satisfaction Analysis." International Journal of Advanced Networking and Applications 14, no. 04 (2023): 5535–40. http://dx.doi.org/10.35444/ijana.2023.14405.

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The field of operations research models known as multi-criteria analysis, also known as Multi-Criteria Decision-Making or Multi-Criteria Satisfaction Analysis deals with the process of making decisions when there are numerous objectives. The conflicting criteria, incomparable units, and challenges in designing/selecting alternatives are all aspects of these methods, which can manage both quantitative and qualitative criteria. The MUSA approach is an ordinal regression analysis-based preference disaggregation model. Based on their values and expressed preferences, the integrated methodology assesses the level of satisfaction of faculty at engineering institutions. The MUSA approach aggregates the various preferences in special satisfaction functions using data from satisfaction surveys. The paper presents a faculty performance analysis by implementing optimization technique known as PSO on Multi Criteria Satisfaction Analysis and shown performance analysis.

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Shahraki, Alireza, and Abbas Jannesari . "Decision Making with Multi Criteria through Hierarchic Analysis Technique and its Effect on Customer Decision Procedure." Information Management and Business Review 4, no. 4 (2012): 153–58. http://dx.doi.org/10.22610/imbr.v4i4.976.

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Today, world competition situation is in a way that organizations need to increase the quality and increase the customer satisfaction, increase the benefit and decrease in outgoings, all at the sometime together. One side, goods prices increase and sever competition in market between goods, and on the other side, complexity in customers attitude and their vary expectations made disaster in management and share increase of the market. So, increase of effects on customer decision procedure as a new attitude in these situations born. Customer decision procedure is a kind of decision- making that is mode by the users. In general, decision-making is recognition processes through selection among different choices. How many criteria are used to analysis by the users? In addition, what kind of criteria do they consider? In addition, to what extent do they emphasize according to their favorites or goods importance. Hierarchic analysis procedure (AHP) is a decision-making with multi criteria that is suitable complex decisions, and consist of decision elements compare in where recognition of quality has encountered with problem. Ranking in decision choices of AHP is to solve the puzzle complexity AHP procedure by finding the specification through different choices, declare good buying decision.

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Azriel, Yazid, and Galuh Saputri. "Sistem Pengambilan Keputusan Pemilihan Menu Terlaris Menggunakan Metode SMART (Simple Multi Attribute Rating Technique)." SAINSTECH: JURNAL PENELITIAN DAN PENGKAJIAN SAINS DAN TEKNOLOGI 33, no. 2 (2023): 26–32. http://dx.doi.org/10.37277/stch.v33i2.1582.

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Abstract In this decision-making system study, SMART (Simple Multi Attribute Rating Technique) is used to select the best-selling menu from all the recommended menus. This multi-criteria decision-making technique is based on the theory that each other method consists of several criteria using a value, and each criterion has a weight that describes its importance compared to other criteria. The SMART method is used to calculate the evaluation criteria, because the SMART approach can work in complex situations and allows analysis with minimal data. . So we need a decision support system that uses the Simple Multi Attribute Rating Technique method to make recommendations for the best menu candidates based on taste test criteria, display tests, presentation tests, and time tests. The end result of this SPK is that we can provide the best recommendations for job seekers according to the specified criteria.  Keywords: Decision support system, Simple Multi Attribute Rating Technique

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Shen, Yung‐Chi, Grace T. R. Lin, and Gwo‐Hshiung Tzeng. "A novel multi‐criteria decision‐making combining Decision Making Trial and Evaluation Laboratory technique for technology evaluation." Foresight 14, no. 2 (2012): 139–53. http://dx.doi.org/10.1108/14636681211222410.

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Türegün, Nida. "Financial performance evaluation by multi-criteria decision-making techniques." Heliyon 8, no. 5 (2022): e09361. http://dx.doi.org/10.1016/j.heliyon.2022.e09361.

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liana, Lalhming, Amitabha Nath, Ch Udaya Bhaskara Rao, and Goutam Saha. "Multi Criteria Decision Making Approach and Clustering Technique for Dam Site Selection." Science & Technology Journal 8, no. 1 (2020): 46–51. http://dx.doi.org/10.22232/stj.2020.08.01.05.

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Identification of dam sites is a strategic priority in water management scheme to preserve and conserve water. The selection of such sites relies on a number of biophysical as well as socio-economic factors. Clustering technique and several Multi Criteria Decision Making (MCDM) approach such as Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) provides valuable tools in the selection of suitable dam sites. This paper presents the application of TOPSIS and k-means clustering technique in the selection of dam site. We have used four criteria in selecting the dam site which were found to be influential criteria in such a problem through literature survey. Eight potential dam sites were selected in Tlawng watershed based on expert opinion and applied TOPSIS and k-means clustering methods to obtain the most ideal solution out of the eight potential dam sites. The computational time of TOPSIS in finding the ideal solution has been reduced when combined with k-means clustering method.

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Abdel Aal, Samah Ibrahim, Shreyas J., and Udayaprasad P. K. "Selecting Optimal Charcoal Company using Multi-Criteria Decision Making Methodology." Multicriteria Algorithms with Applications 3 (March 12, 2024): 15–22. http://dx.doi.org/10.61356/j.mawa.2024.311561.

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A popular technique used in many industries to assist decision-makers in evaluating and selecting the best alternatives from a variety of accessible possibilities is multi-criteria decision-making (MCDM). This study proposed an MCDM methodology for selecting optimal charcoal from various options and criteria. Various criteria influence the selection problem, such as financial, safety, labour, power supply, production, and transportation. This study used the Combinative Distance Assessment (CODAS) method as an MCDM method to rank the alternatives and use the best one. This study used nine criteria and twenty alternatives. The requirements are divided into positive and negative criteria to compete for the positive and negative ideal solution using the CODAS method. The criteria weights are computed. The rank of alternatives is checked by using the sensitivity analysis. The results show the rank of other options is stable in different cases.

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Farid, Hafiz Muhammad Athar, Muhammad Riaz, and Gustavo Santos Garcia. "T-spherical fuzzy information aggregation with multi-criteria decision-making." AIMS Mathematics 8, no. 5 (2023): 10113–45. http://dx.doi.org/10.3934/math.2023512.

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<abstract><p>T-spherical fuzzy sets (T-SPFSs) have gained popularity because of their ability to account for uncertainty more effectively and spanning a larger domain. The sum of the t-$ th $ power of membership grades in T-SPFSs is close to a unit interval, allowing for greater uncertainty. As a result, this set outperforms traditional fuzzy structures. The "multi-criteria decision-making" (MCDM) approach is a widely used technique that requires the use of some aggregation tools, and various such aggregation operators (AOs) have been developed over the years to achieve this purpose. The purpose of this paper is to propose some new operational laws and AOs for use in a T-spherical fuzzy environment. In this regard, we presented some new neutral or fair operational rules that combine the concept of proportional distribution to provide a neutral or fair solution to the membership, abstinence, and non-membership of T-spherical fuzzy numbers (T-SPFNs). Based on the obtained operational rules, we presented the "T-spherical fuzzy fairly weighted average operator" and the "T-spherical fuzzy fairly ordered weighted averaging operator". Compared to earlier methodologies, the proposed AOs provide more generalised, reliable, and accurate information. In addition, under T-SPFSs, an MCDM approach is developed employing suggested AOs with several decision-makers (DMs) and partial weight details. Finally, to demonstrate the applicability of the innovative technique, we give an actual case study of "food waste treatment technology" (FWTT) selection under T-SPFSs scenarios. A comparison with an existing model has also been undertaken to confirm the validity and robustness of the acquired results.</p></abstract>

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Taherdoost, Hamed, and Atefeh Mohebi. "A Comprehensive Guide to the COPRAS method for Multi-Criteria Decision Making." Journal of Management Science & Engineering Research 7, no. 2 (2024): 1–14. http://dx.doi.org/10.30564/jmser.v7i2.6280.

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MCDM has been utilized as a proficient decision-making technique for numerous decades. Complex Proportional Assessment (COPRAS) method, a prominent technique in multi-criteria decision-making (MCDM) which offers a systematic and effective framework for evaluating alternatives and making informed choices. The versatility of COPRAS is demonstrated via case studies across various domains, such as engineering, business, and environmental management, showcasing its adaptability and robustness in providing solutions to diverse decision-making scenarios. There is a lack of a comprehensive guide and a reviewing of application, strengths, and limitation for this method in the literature. Therefore, this study aims to offer an in-depth understanding of the COPRAS approach, including its applications, advantages, and disadvantages. Additionally, it provides detailed guidance on how to utilize the COPRAS methodology for decision-making and real-life problems.

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Manoj, Vasupalli, Ramana Pilla, and Vasudeva Naidu Pudi. "Sustainability Performance Evaluation of Solar Panels Using Multi Criteria Decision Making Techniques." Journal of Physics: Conference Series 2570, no. 1 (2023): 012014. http://dx.doi.org/10.1088/1742-6596/2570/1/012014.

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Abstract Researchers from all around the world had worked tirelessly to find ways to lower the cost of solar panels, create more efficient new goods, boost their fuel efficiency, and create innovations and largely dependent on photovoltaic system technology. When compared to other forms of non-conventional energy, such as wind and tidal, solar has been one of the most widely employed resources. To harness the power of the sun using photovoltaics, one needs a photovoltaic system. Research into improving the cost-effectiveness of solar panels, which play a crucial part in photovoltaic systems, is a global endeavour. The process of choosing solar panels is nuanced, encompassing a wide range of subjective and objective considerations. To choose the best solar cell for a PV array, we use the VIKOR (VIekriterijumsko KOmpromisno Rangiranje) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) techniques. Using the Analytical Hierarchy Process (AHP) and a resemblance to ideal result ordering technique, the study’s goals were satisfied. VIKOR and other MCDM tools like the AHP and TOPSIS are used to rank candidates in terms of performance. An in-depth case study was conducted using six different kinds of solar panels to show how well the approaches work.

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Setyadi, Heribertus Ary, and Doddy Satrya Perbawa. "ELECTRIC BICYCLE SELECTION SYSTEM USING MULTI CRITERIA DECISION MAKING." JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) 10, no. 1 (2024): 142–51. http://dx.doi.org/10.33480/jitk.v10i1.5163.

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Indonesia government has targeted that by 2025 electric vehicle production has reached 20%. Many electric bicycle products have been sold and used in Indonesia, both domestically made and imported. The most important technical considerations in choosing an electric bicycle are battery type and motor used. These two components affect distance traveled by electric bicycles even further. Many brands offered by manufacturers with various advantages and disadvantages will make consumers are confused about choosing a quality and durable electric bicycle. From these problems, one solution is to create a mobile-based decision support system (DSS) that can assist in making decisions according to predetermined criteria. This research aims to produce recommendations for electric bicycle brands that can assist potential consumers in choosing electric bicycles. The combination of the Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods is used in order to produce more objective recommendations. In this research uses seven criteria that will be processed in AHP, namely price, maximum load, battery capacity, motor power, charging time, mileage and speed. There are nine brands that are used as alternatives in the TOPSIS calculation. From AHP and TOPSIS calculation, following recommendations for electric bicycles is obtained: the first order is the Ofero with a preference value of 1, next order are with the same value 0.5806, Indobike and Exotic, and the last recommendation is Jarvis with a value of 0.095.

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Taherdoost, Hamed, and Mitra Madanchian. "An Effective Compromising Ranking Technique for Decision Making." Macro Management & Public Policies 5, no. 2 (2023): 27–33. http://dx.doi.org/10.30564/mmpp.v5i2.5578.

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The VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method, which is a multi-criteria decision-making method, is examined in this paper. The VIKOR method, like other MCDM techniques such as the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is widely used to solve complex decision-making problems in various fields such as engineering, management, and finance. This paper provides an overview of the VIKOR method, including its application areas, advantages, and disadvantages. Besides, in this survey paper, the process steps of the VIKOR method are described, including determining the decision matrix, normalizing the matrix, determining the weights of the criteria, calculating the utility and regret values, calculating the VIKOR index, and finally ranking the alternatives. By providing an overview of the VIKOR method and its process steps, this paper aims to provide a better understanding of the method and its potential application in different decision-making contexts.

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Senapati, Tapan, Ronald R. Yager, and Guiyun Chen. "Cubic intuitionistic WASPAS technique and its application in multi-criteria decision-making." Journal of Ambient Intelligence and Humanized Computing 12, no. 9 (2021): 8823–33. http://dx.doi.org/10.1007/s12652-020-02667-8.

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Journal articles on the topic 'Multi-criteria decision making technique'

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