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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 (December 23, 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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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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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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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 (June 21, 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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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 (November 22, 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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Francik, Sławomir, Norbert Pedryc, Adrian Knapczyk, Artur Wójcik, Renata Francik, and Bogusława Łapczyńska-Kordon. "Bibliometric analysis of multiple criteria decision making in agriculture." Technical Sciences 1, no. 20 (December 15, 2016): 17–30. http://dx.doi.org/10.31648/ts.2906.
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Development trends (Research Trends) in scientific research on the methods of Multiple Criteria Decision Making (MCDM) and Multiple Criteria Decision Analysis (MCDA) in agriculture are analyzed. Established bibliometric techniques are applied. MCDA/MCDM methods are being very intensively developed in recent years, as evidenced by the number of scientific papers published annually in renowned scientific journals indexed in the Web of Science (WoS) database. In the years 1979-2015 a total of 1,355 scientific articles were collected in the database. The number of articles published annually increased rapidly after 2005. Besides, the annual number of citations of the publications is increasing. Research on MCDA/MCDM is conducted in many research areas. In the years 1984-2015 the Web of Science database accumulated 27 scientific publications on MCDA/MCDM in agriculture area. Therefore, it can be concluded that the MCDA/MCDM issues are currently not sufficiently analyzed in relation to agriculture. In the future this subject will probably be further developed, an increasing number of scientists will conduct research on the MCDA/MCDM and the annual number of articles published in the field will increase.
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Sikder, Abu Hena Mustafa Kamal, and Mashfiqus Salehin. "Multi-criteria decision making methods for rural water supply: a case study from Bangladesh." Water Policy 17, no. 6 (June 3, 2015): 1209–23. http://dx.doi.org/10.2166/wp.2015.111.
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Multiple criteria decision making (MCDM) is a process of evaluating alternatives against relevant decision making criteria. Several methods are available to facilitate the evaluation steps. This paper deals with a rural water supply problem in the coastal areas of Bangladesh. Three different MCDM methods – weighted summation, analytical hierarchy process, and novel approach to imprecise assessment and decision environments – were used to evaluate the suitable water supply alternative. The ranking of alternatives obtained from these MCDM techniques produced similar results. Among five water supply alternatives evaluated, rainwater harvesting systems and deep tube wells scored first and second, respectively, for all three evaluation methods. In addition, sensitivity analyses were carried out for the MCDM techniques and these results did not show drastic variations either. This finding implies that while selection of MCDM technique is important, when evaluating similar problems more emphasis should be given to defining the problem comprehensively and thus selecting the relevant criteria and priorities to factor into the decision problem.
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Zavadskas, Edmundas Kazimieras, Dragan Pamučar, Željko Stević, and Abbas Mardani. "Multi-Criteria Decision-Making Techniques for Improvement Sustainability Engineering Processes." Symmetry 12, no. 6 (June 9, 2020): 986. http://dx.doi.org/10.3390/sym12060986.
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The success of any activity and process depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction. That is, the ability to properly define a set of success indicators. The application of the developed new multi-criteria decision-making (MCDM) methods can be eliminated or decreased by decision-makers’ subjectivity, which leads to consistency or symmetry in the weight values of the criteria. In this Special Issue, 40 research papers and one review study co-authored by 137 researchers from 23 different countries explore aspects of multi-criteria modeling and optimization in crisp or uncertain environments. The papers proposing new approaches and elaborate case studies in the following areas of applications: MCDM optimization in sustainable engineering, environmental sustainability in engineering processes, sustainable multi-criteria production and logistics processes planning, integrated approach for modeling processes in engineering, new trends in the multi-criteria evaluation of sustainable processes, multi-criteria decision-making in strategic management based on sustainable criteria.
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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 (July 2, 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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Balogun, A. O., A. O. Bajeh, H. A. Mojeed, and A. G. Akintola. "Software defect prediction: A multi-criteria decision-making approach." Nigerian Journal of Technological Research 15, no. 1 (April 30, 2020): 35–42. http://dx.doi.org/10.4314/njtr.v15i1.7.
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Failure of software systems as a result of software testing is very much rampant as modern software systems are large and complex. Software testing which is an integral part of the software development life cycle (SDLC), consumes both human and capital resources. As such, software defect prediction (SDP) mechanisms are deployed to strengthen the software testing phase in SDLC by predicting defect prone modules or components in software systems. Machine learning models are used for developing the SDP models with great successes achieved. Moreover, some studies have highlighted that a combination of machine learning models as a form of an ensemble is better than single SDP models in terms of prediction accuracy. However, the efficiency of machine learning models can change with diverse predictive evaluation metrics. Thus, more studies are needed to establish the effectiveness of ensemble SDP models over single SDP models. This study proposes the deployment of Multi-Criteria Decision Method (MCDM) techniques to rank machine learning models. Analytic Network Process (ANP) and Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE) which are types of MCDM techniques are deployed on 9 machine learning models with 11 performance evaluation metrics and 11 software defects datasets. The experimental results showed that ensemble SDP models are best appropriate SDP models as Boosted SMO and Boosted PART ranked highest for each of the MCDM techniques. Besides, the experimental results also validated the stand of not considering accuracy as the only performance evaluation metrics for SDP models. Conclusively, more performance metrics other than predictive accuracy should be considered when ranking and evaluating machine learning models.
Keywords: Ensemble; Multi-Criteria Decision Method; Software Defect Prediction
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Al-Sakkaf, Abobakr, Moaaz Elkabalawy, and Eslam Mohammed Abdelkader. "Synthetic Evaluation of Multi-Criteria Decision-Making Algorithms in Energy-Efficient Buildings." International Journal of Strategic Decision Sciences 13, no. 1 (January 1, 2022): 1–13. http://dx.doi.org/10.4018/ijsds.309120.
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Multi-criteria decision making (MCDM) on energy-efficient buildings has become essential in both the industry and academia as construction projects grow increasingly complex. With a prime goal of increasing its effectiveness, MCDM research has witnessed tremendous growth over the past three decades. Despite the necessity to monitor the research growth of a research topic to identify its trends and gaps, and hence shed light on research areas that warrant future research attention, there is a lack of systematic literature analysis in MCDM area. To fill this gap, this paper recruited a mixed-review method of scientometric and systematic reviews of 56 research papers on seven selected popular MCDM techniques published from 2010 to March 2021. The scientometric review identified the most prolific journals, keyword correlations, and geospatial connections between research countries in the MCDM area. On the other hand, the systematic review analysis showed that there are five main research topics in MCDM. Furthermore, the major approaches applied in MCDM research were investigated.
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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 (March 2, 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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Zavadskas, Edmundas Kazimieras, Zenonas Turskis, and Simona Kildienė. "STATE OF ART SURVEYS OF OVERVIEWS ON MCDM/MADM METHODS." Technological and Economic Development of Economy 20, no. 1 (March 26, 2014): 165–79. http://dx.doi.org/10.3846/20294913.2014.892037.
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Decision-making is primarily a process that involves different actors: people, groups of people, institutions and the state. As a discipline, multi-criteria decision-making has a relatively short history. Since 1950s and 1960s, when foundations of modern multi-criteria decision-making methods have been laid, many researches devoted their time to development of new multi-criteria decision-making models and techniques. In the past decades, researches and development in the field have accelerated and seem to continue growing exponentially. Despite the intensive development worldwide, few attempts have been made to systematically present the theoretical bases and developments of multi-criteria decision-making methods. However, the methodological choices and framework for assessment of decisions are still under discussion. The article describes the situation with reviews of MCDM/MADM methods. Furthermore, there is a need for research to study the strengths and weaknesses of different decision-making methods.
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Bairagi, Bipradas. "Technique of Accurate Ranking Order (TARO): A novel multi criteria analysis approach in performance evaluation of industrial robots for material handling." Decision Science Letters 11, no. 4 (2022): 563–89. http://dx.doi.org/10.5267/j.dsl.2022.5.001.
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Rank reversal in decision making is a common phenomenon resulting in confusion and ambiguity in selection procedure especially while multiple multi-criteria decision making (MCDM) techniques are independently applied. To eradicate this confusion, this paper proposes a novel MCDM methodology namely Technique of Accurate Ranking Order (TARO). The TARO method is an extension of conventional MCDM approaches. The proposed method commences at the end of conventional methodologies with the final selection values. The proposed technique, using an advanced version of entropy weighting method, initially measures weights of the final selection values. Subsequently, based on the final section values and their computed weights, TARO measures accurate selection indices that determine the accurate ranking order of the alternatives. The proposed technique is illustrated by three real life examples on robot selection problems. The results obtained by TARO justify the validity, applicability and requirements of the proposed techniques for proper decision making under the MCDM environment.
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Ghorabaee, Mehdi Keshavarz, Edmundas Kazimieras Zavadskas, Maghsoud Amiri, and Zenonas Turskis. "Extended EDAS Method for Fuzzy Multi-criteria Decision-making: An Application to Supplier Selection." International Journal of Computers Communications & Control 11, no. 3 (March 24, 2016): 358. http://dx.doi.org/10.15837/ijccc.2016.3.2557.
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In the real-world problems, we are likely confronted with some alternatives that eed to be evaluated with respect to multiple conflicting criteria. Multi-criteria ecision-making (MCDM) refers to making decisions in such a situation. There are any methods and techniques available for solving MCDM problems. The evaluation ased on distance from average solution (EDAS) method is an efficient multi-criteria ecision-making method. Because the uncertainty is usually an inevitable part of he MCDM problems, fuzzy MCDM methods can be very useful for dealing with the eal-world decision-making problems. In this study, we extend the EDAS method o handle the MCDM problems in the fuzzy environment. A case study of supplier election is used to show the procedure of the proposed method and applicability of t. Also, we perform a sensitivity analysis by using simulated weights for criteria to xamine the stability and validity of the results of the proposed method. The results f this study show that the extended fuzzy EDAS method is efficient and has good tability for solving MCDM problems.
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Paul, Ananna, Nagesh Shukla, Sanjoy Kumar Paul, and Andrea Trianni. "Sustainable Supply Chain Management and Multi-Criteria Decision-Making Methods: A Systematic Review." Sustainability 13, no. 13 (June 24, 2021): 7104. http://dx.doi.org/10.3390/su13137104.
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Multi-criteria decision-making (MCDM) methods are smart tools to deal with numerous criteria in decision-making. These methods have been widely applied in the area of sustainable supply chain management (SSCM) because of their computational capabilities. This paper conducts a systematic literature review on MCDM methods applied in different areas of SSCM. From the literature search, a total of 106 published journal articles have been selected and analyzed. Both individual and integrated MCDM methods applied in SSCM are reviewed and summarized. In addition, contributions, methodological focuses, and findings of the reviewed articles are discussed. It is observed that MCDM methods are widely used for analyzing barriers, challenges, drivers, enablers, criteria, performances, and practices of SSCM. In recent years, studies have focused on integrating more than one MCDM method to highlight methodological contributions in SSCM; however, in the literature, limited research papers integrate multiple MCDM methods in the area of SSCM. Most of the published articles integrate only two MCDM methods, and integration with other methods, such as optimization and simulation techniques, is missing in the literature. This review paper contributes to the literature by analyzing existing research, identifying research gaps, and proposing new future research opportunities in the area of sustainable supply chain management applying MCDM methods.
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Shaikh, Salman Ahmed, Mohsin Memon, and Kyoung-Sook Kim. "A Multi-Criteria Decision-Making Approach for Ideal Business Location Identification." Applied Sciences 11, no. 11 (May 28, 2021): 4983. http://dx.doi.org/10.3390/app11114983.
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Location has always been a primary concern for business startups to be successful. Therefore, much research has focused on the problem of identification of an ideal business site for a new business. The process of ideal business site selection is complex and depends on a number of criteria or factors. Since the ultimate goal of all businesses is to increase customer footprints and to thus increase sales, criteria including traffic accessibility, visibility, ease of access, vehicle parking, customers availability, etc. play important roles. In other words, we can say that optimal business site selection is a multi-criteria decision-making (MCDM) problem. MCDM is used to identify an optimal solution or decision out of many alternatives by utilizing a number of criteria. In mathematics, there exist a number of structured techniques for organizing and analyzing complex decisions, for instance, AHP, ANP, TOPSIS, etc. In this work, we present a hybrid of two such techniques to solve the MCDM problem for an optimal business site selection given a set of candidate sites. The proposed approach is based on the AHP (Analytic Hierarchy Process) and TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) approaches. The reason for using the proposed hybrid approach is multi-fold. The hybrid approach reduces the computational complexity and require less manual effort, thus improving the efficiency and accuracy of the proposed approach. Given a set of candidate locations for a new business, the proposed approach ranks the candidates. Thus, the candidate locations with higher ranks are identified as suitable or ideal. The approach comes up with the ranking of all of the candidate locations, thus giving business managers room to make calculated decisions. To show the effectiveness of the proposed approach, a detailed step-by-step case study is given to identify an ideal location in New York City for a new gas station. Furthermore, an experimental evaluation is also presented using a number of real New York City datasets.
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Saima Anwar, Sana Akhtar, and Gra Badshah. "Evaluation of Active Queue Management Methods based on Integrated AHP, TOPSIS and Fuzzy TOPSIS." Journal of Computing & Biomedical Informatics 3, no. 01 (March 15, 2022): 267–81. http://dx.doi.org/10.56979/301/2022/39.
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The Evaluation and selection of Active Queue Management (AQM) methods are a complicated and challenging task. Improper AQM method can cause up-mark and network malfunctioning. To achieve satisfactory performance, various evaluation criteria need to be considered. In order to find the limitations of how the criteria are determined, there is a need to find out how their procedures change according to the evaluation and benchmarking process of AQM. This article focuses on the evaluation and benchmarking of Active Queue Management methods using Multi-Criteria Decision-Making (MCDM) techniques. MCDM uses different techniques to figure out the best alternative from multi-criteria and multi alternative conditions. Analytic Hierarchy Process (AHP) is a multi-criteria decision-making technique that is used to assign weights to criteria. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking and selection of different alternatives by using distance measures. Whereas, FUZZY TOPSIS is used for criteria weightage and alternatives rating. MCDM calculation is performed on AQM methods and it is tried to discuss all these techniques. MCDM uses performance, overhead, and configuration criteria to evaluate and select the best AQM method that helps to determine solutions for future directions. The results show that Random Early Detection (RED) method got higher ranking score records as compared to other AQM methods.
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Guebsi, Wafa, and Alaeddine Zouari. "Investigation on Multi-Criteria Decision Making Methods Application in Sustainable Product Design." SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi dan Aplikasi) 3, no. 1 (June 14, 2022): 91–104. http://dx.doi.org/10.12928/spekta.v3i1.5962.
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Background: Integrating sustainability development' aspects in the design process is becoming, a growth area in companies. Consequently, sustainable product design has to consider the different aspects of sustainability throughout its life cycle phases in addition of other requirements. This integration is becoming more complicated due the difficulty of managing the constraints and alternatives related to the product and stakeholders needs. This study aims to highlights the most used Multi-Criteria Decision Making (MCDM) tools and methods used in sustainable product design process. Contribution: Product design process involves interesting decisional tasks such as the choice of materials, standard parts, technical solutions. Hence, the contribution of this work is to help designer to adopt relevant MCDM tools and methods that can be integrated to other tools to facilitate and to justify their decisional tasks. Method: Several methods have been affected to solve the problems related to this complexity such as MCDM. A literature review was conducted based on Siencedirect and GoogleScholar articles databases. After filtering more than 200 articles only 62 articles were considered to analyze the correlation between sustainable product design and MCDM. Results: Classified MCDM use according to the type of choices to achieve SPD goals. This paper allowed us to find matches between MCDM methods and SPD problem. The majority of case studies result show that a large portion of sustainable design methods, techniques, and tools are applied to the sustainable product’ along its different life cycle phases Conclusion: It is noticed that the use of MCDM methods are an important outcome in the sustainable product design process and deeply helps designers to make suitable choices. Also, several matches relating MCDM, other methods and sustainable product design sphere are discussed
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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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Rajabi, Fazel, Hossein Molaeifar, Mehdi Jahangiri, Shekofeh Taheri, Sean Banaee, and Payam Farhadi. "Occupational stressors among firefighters: application of multi-criteria decision making (MCDM)Techniques." Heliyon 6, no. 4 (April 2020): e03820. http://dx.doi.org/10.1016/j.heliyon.2020.e03820.
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Kazimieras Zavadskas, Edmundas, Jurgita Antucheviciene, and Prasenjit Chatterjee. "Multiple-Criteria Decision-Making (MCDM) Techniques for Business Processes Information Management." Information 10, no. 1 (December 23, 2018): 4. http://dx.doi.org/10.3390/info10010004.
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Information management is a common paradigm in modern decision-making. A wide range of decision-making techniques have been proposed in the literature to model complex business processes. In this Special Issue, 16 selected and peer-reviewed original research articles contribute to business information management in various current real-world problems by proposing crisp or uncertain multiple-criteria decision-making (MCDM) models and techniques, mostly including multi-attribute decision-making (MADM) approaches in addition to a single paper proposing an interactive multi-objective decision-making (MODM) approach. The papers are mainly concentrated in three application areas: supplier selection and rational order allocation, the evaluation and selection of goods or facilities, and personnel selection/partner selection. A number of new approaches are proposed that are expected to attract great interest from the research community.
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Mhlanga, Sandile Thamie, and Manoj Lall. "Influence of Normalization Techniques on Multi-criteria Decision-making Methods." Journal of Physics: Conference Series 2224, no. 1 (April 1, 2022): 012076. http://dx.doi.org/10.1088/1742-6596/2224/1/012076.
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Abstract One of the most significant steps in solving multi criteria decision-making (MCDM) problems is the normalization of the decision matrix. The consideration for the normalization of the data in a judgment matrix is an essential step as it can influence the ranking list. This study investigates the effects of normalization on an AHP-VIKOR hybrid method in the selection of Web services. The Web services considered in this research offer similar functionalities but with different Quality of Services (QoS). For the purpose of this study, ten web services were selected. Each of these services were evaluated against five difference QoS requirements namely, response time, throughput rate, latency, availability, and reliability to determine the most appropriate Web services. The five normalization techniques employed are linear sum, linear max, linear max-min, enhanced accuracy and vector normalization. It was observed that different ranking lists are produced when applying different normalization techniques to the VIKOR method and normalization has an influence on the final ranking list.
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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 (January 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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Ogrodnik, Karolina. "Multi-Criteria Analysis of Design Solutions in Architecture and Engineering: Review of Applications and a Case Study." Buildings 9, no. 12 (December 17, 2019): 244. http://dx.doi.org/10.3390/buildings9120244.
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The primary goal of this paper is to present the application potential of MCDM/MCDA (multi-criteria decision-making/multi-criteria decision analysis) methods in the field of architecture and urban planning and in energy efficient construction, especially in the context of sustainable development paradigm. The first part of this paper is devoted to literature studies pertaining to multi-criteria decision-making support in the selected fields. On the basis of the delivered review, it was demonstrated that the most popular methods belonging to the MCDM/MCDA group that have been used so far for the purpose of resolving selected decision-making challenges, is the AHP (analytic hierarchy process) method with modifications, TOPSIS (technique for order of preference by similarity to ideal solution) method, as well the up-and-coming COPRAS (complex proportional assessment) method. In addition, by reviewing the literature, it was found that MCDM/MCDA methods constitute an effective support tool at the stage of evaluating and selecting project solutions, and are especially helpful in framing various social, economic, environmental criteria that are permanently linked to the rule of sustainable development. The empirical section of this paper, through a case study, presents a comparative analysis of the classical AHP method with its extension onto fuzzy sets. The case study pertained to the criteria for the location of single-family residential buildings with solar installations.
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Hashmi, Masooma Raza, Syeda Tayyba Tehrim, Muhammad Riaz, Dragan Pamucar, and Goran Cirovic. "Spherical Linear Diophantine Fuzzy Soft Rough Sets with Multi-Criteria Decision Making." Axioms 10, no. 3 (August 13, 2021): 185. http://dx.doi.org/10.3390/axioms10030185.
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Modeling uncertainties with spherical linear Diophantine fuzzy sets (SLDFSs) is a robust approach towards engineering, information management, medicine, multi-criteria decision-making (MCDM) applications. The existing concepts of neutrosophic sets (NSs), picture fuzzy sets (PFSs), and spherical fuzzy sets (SFSs) are strong models for MCDM. Nevertheless, these models have certain limitations for three indexes, satisfaction (membership), dissatisfaction (non-membership), refusal/abstain (indeterminacy) grades. A SLDFS with the use of reference parameters becomes an advanced approach to deal with uncertainties in MCDM and to remove strict limitations of above grades. In this approach the decision makers (DMs) have the freedom for the selection of above three indexes in [0,1]. The addition of reference parameters with three index/grades is a more effective approach to analyze DMs opinion. We discuss the concept of spherical linear Diophantine fuzzy numbers (SLDFNs) and certain properties of SLDFSs and SLDFNs. These concepts are illustrated by examples and graphical representation. Some score functions for comparison of LDFNs are developed. We introduce the novel concepts of spherical linear Diophantine fuzzy soft rough set (SLDFSRS) and spherical linear Diophantine fuzzy soft approximation space. The proposed model of SLDFSRS is a robust hybrid model of SLDFS, soft set, and rough set. We develop new algorithms for MCDM of suitable clean energy technology. We use the concepts of score functions, reduct, and core for the optimal decision. A brief comparative analysis of the proposed approach with some existing techniques is established to indicate the validity, flexibility, and superiority of the suggested MCDM approach.
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Hagag, Asmaa M., Laila S. Yousef, and Tamer F. Abdelmaguid. "Multi-Criteria Decision-Making for Machine Selection in Manufacturing and Construction: Recent Trends." Mathematics 11, no. 3 (January 26, 2023): 631. http://dx.doi.org/10.3390/math11030631.
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As the number of alternative machines has increased and their technology has been continuously developed, the machine selection problem has attracted many researchers. This article reviews recent developments in applying multi-criteria decision-making (MCDM) methods for selecting machines in the manufacturing and construction industries. Selected articles are classified according to the application area and the applied MCDM method. By focusing on the last five years, this paper identifies recent trends in developing and using these methods. Results suggest that there has been a noticeable growth in the utilization of MCDM techniques for machine selection problems in both sectors. It is also noted that several decision-support tools and methods have been developed and successfully applied during this period. Accordingly, needs and directions for future research are discussed.
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Siksnelyte, Indre, Edmundas Zavadskas, Dalia Streimikiene, and Deepak Sharma. "An Overview of Multi-Criteria Decision-Making Methods in Dealing with Sustainable Energy Development Issues." Energies 11, no. 10 (October 15, 2018): 2754. http://dx.doi.org/10.3390/en11102754.
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The measurement of sustainability is actively used today as one of the main preventative instruments in order to reduce the decline of the environment. Sustainable decision-making in solving energy issues can be supported and contradictory effects can be evaluated by scientific achievements of multi-criteria decision-making (MCDM) techniques. The main goal of this paper is to overview the application of decision-making methods in dealing with sustainable energy development issues. In this study, 105 published papers from the Web of Science Core Collection (WSCC) database are selected and reviewed, from 2004 to 2017, related to energy sustainability issues and MCDM methods. All the selected papers were categorized into 9 fields by the application area and into 10 fields by the used method. After the categorization of the scientific articles and detailed analysis, SWOT analysis of MCDM approaches in dealing with sustainable energy development issues is provided. The widespread application and use of MCDM methods confirm that MCDM methods can help decision-makers in solving energy sustainability problems and are highly popular and used in practice.
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Ayasrah, Omar, and Faiz Mohd Turan. "Multi-Criteria Decision-Making Model using Intuitionistic Fuzzy Entropy and Variable Weight Theory." MEKATRONIKA 3, no. 1 (June 16, 2021): 18–25. http://dx.doi.org/10.15282/mekatronika.v3i1.7025.
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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.
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Vasegaard, Alex Elkjær, Mathieu Picard, Florent Hennart, Peter Nielsen, and Subrata Saha. "Multi Criteria Decision Making for the Multi-Satellite Image Acquisition Scheduling Problem." Sensors 20, no. 5 (February 25, 2020): 1242. http://dx.doi.org/10.3390/s20051242.
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The multi-satellite image acquisition scheduling problem is traditionally seen as a complex optimization problem containing a generic objective function that represents the priority structure of the satellite operator. However, the majority of literature neglect the collective and contemporary effect of factors associated with the operational goal in the objective function, i.e., uncertainty in cloud cover, customer priority, image quality criteria, etc. Consequently, the focus of the article is to integrate a real-time scoring approach of imaging attempts that considers these aspects. This is accomplished in a multi-satellite planning environment, through the utilization of the multi-criteria decision making (MCDM) models, Elimination and Choice Expressing Reality (ELECTRE-III) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and the formulation of a binary linear programming model. The two scoring approaches belong to different model classes of MCDM, respectively an outranking approach and a distance to ideal point approach, and they are compared with a naive approach. Numerical experiments are conducted to validate the models and illustrate the importance of criteria neglected in previous studies. The results demonstrate the customized behaviour allowed by MCDM methods, especially the ELECTRE-III approach.
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Alam, Md Moshiul, Roslina Mohammad, and Friha Anjum Hira. "SELECTION OF ALTERNATIVE MARINE FUEL TECHNOLOGY BASED ON LITERATURE REVIEW BY APPLYING APPROPRIATE MULTI-CRITERIA DECISION-MAKING METHOD." Journal of Science, Technology and Innovation Policy 7, no. 2 (December 29, 2021): 1–12. http://dx.doi.org/10.11113/jostip.v7n2.83.
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The use of alternative fuel in ships can help alleviate high carbon emissions and adverse environmental consequences produced by the maritime industry. Due to the complexity of assessing many performance factors and lack of information, it is challenging for decision-makers to select the best sustainable alternative energy source for shipping from various options. Nevertheless, alternative energy decisions can be supported, and contradicting impacts can be analyzed with MCDM methodologies. This study focuses on applying decision-making processes for sustainable energy development concerns. A systematic review of published papers in the Scopus database on alternative fuel technologies and MCDM approaches from 2001 to 2021 has been conducted. All the selected articles were sorted by application area and process. In classifying the scientific journal articles and in-depth analysis, a SWOT analysis of MCDM techniques is offered. Convincing data support the conclusion that MCDM methods help decision-makers select appropriate fuel technology and are widely utilized in practice.
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Feng, Yixiong, Zhifeng Zhang, Guangdong Tian, Amir Mohammad Fathollahi-Fard, Nannan Hao, Zhiwu Li, Wenjie Wang, and Jianrong Tan. "A Novel Hybrid Fuzzy Grey TOPSIS Method: Supplier Evaluation of a Collaborative Manufacturing Enterprise." Applied Sciences 9, no. 18 (September 9, 2019): 3770. http://dx.doi.org/10.3390/app9183770.
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Recently, there is of significant interest in developing multi-criteria decision making (MCDM) techniques with large applications for real-life problems. Making a reasonable and accurate decision on MCDM problems can help develop enterprises better. The existing MCDM methods, such as the grey comprehensive evaluation (GCE) method and the technique for order preference by similarity to an ideal solution (TOPSIS), have their one-sidedness and shortcomings. They neither consider the difference of shape and the distance of the evaluation sequence of alternatives simultaneously nor deal with the interaction that universally exists among criteria. Furthermore, some enterprises cannot consult the best professional expert, which leads to inappropriate decisions. These reasons motivate us to contribute a novel hybrid MCDM technique called the grey fuzzy TOPSIS (FGT). It applies fuzzy measures and fuzzy integral to express and integrate the interaction among criteria, respectively. Fuzzy numbers are employed to help the experts to make more reasonable and accurate evaluations. The GCE method and the TOPSIS are combined to improve their one-sidedness. A case study of supplier evaluation of a collaborative manufacturing enterprise verifies the effectiveness of the hybrid method. The evaluation result of different methods shows that the proposed approach overcomes the shortcomings of GCE and TOPSIS. The proposed hybrid decision-making model provides a more accurate and reliable method for evaluating the fuzzy system MCDM problems with interaction criteria.
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Wu, Zhen, and Georges Abdul-Nour. "Comparison of Multi-Criteria Group Decision-Making Methods for Urban Sewer Network Plan Selection." CivilEng 1, no. 1 (June 16, 2020): 26–48. http://dx.doi.org/10.3390/civileng1010003.
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Selecting a suitable sewer network plan for a city is a complex and challenging task that requires discussion among a group of experts and the consideration of multiple conflicting criteria with different measurement units. A number of multi-criteria decision-making (MCDM) methods have been proposed for analyzing sewer network selection problems, each having their own distinct advantages and limitations. Although many decision-making techniques are available, decision-makers are confronted with the difficult task of selecting the appropriate MCDM method, as each method can lead to different results when applied to an identical problem. This paper evaluates four different multi-criteria decision-making methods, which are the Analytic Hierarchy Process (AHP), the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Elimination Et Choix Traduisant la REalité (ELECTRE III) and the Preference Ranking Organization METHods for Enrichment Evaluations II (PROMETHEE II), for one sewer network group decision problem in the early stage of sewer water infrastructure asset management. Moreover, during the implementation of different MCDM methods, the Delphi technique is introduced to organize and structure the discussions among all the decision-makers. The results of the study are examined based on each method’s ability to provide accurate representations of the decision-makers’ preferences and their experience implementing each method. As a conclusion, decision-makers identify PROMETHEE II as their favorite method, AHP is more time and energy consuming and results in a number of inconsistencies, while TOPSIS loses information during vector normalization for multi-dimension criteria, and ELECTRE III’s results are inconclusive.
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Yazdani-Chamzini, Abdolreza, Mohammad Majid Fouladgar, Edmundas Kazimieras Zavadskas, and S. Hamzeh Haji Moini. "SELECTING THE OPTIMAL RENEWABLE ENERGY USING MULTI CRITERIA DECISION MAKING." Journal of Business Economics and Management 14, no. 5 (September 23, 2013): 957–78. http://dx.doi.org/10.3846/16111699.2013.766257.
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Renewable energies are well-known as one of the most important energy resources not only due to limited other energy resources, but also due to environmental problems associated with air pollutants and greenhouse gas emissions. Renewable energy project selection is a multi actors and sophisticated problem because it is a need to incorporate social, economic, technological, and environmental considerations. Multi criteria decision making (MCDM) methods are powerful tools to evaluate and rank the alternatives among a pool of alternatives and select the best one. COPRAS (COmplex PRoportional ASsessment) is an MCDM technique which determines the best alternative by calculating the ratio to the ideal solution and the negative ideal solution. On the other hand, analytical hierarchy process (AHP) is widely used in order to calculate the importance weights of evaluation criteria. In this paper an integrated COPRAS-AHP methodology is proposed to select the best renewable energy project. In order to validate the output of the proposed model, the model is compared with five MCDM tools. The results of this paper demonstrate the capability and effectiveness of the proposed model in selecting the most appropriate renewable energy option among the existing alternatives.
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Hajduk, Sławomira. "Multi-Criteria Analysis of Smart Cities on the Example of the Polish Cities." Resources 10, no. 5 (May 8, 2021): 44. http://dx.doi.org/10.3390/resources10050044.
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This paper presents the application of a Multi-Criteria Decision Making (MCDM) method for the ranking of smart cities. During the construction of the MCDM techniques, the importance of the decision-making approach for the linear ordering of 66 Polish cities with powiat status was presented. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) was used for evaluation. The method has been verified by applying it to measure urban smartness. The TOPSIS method allowed compilation for a final ranking, taking into account publicly available indicators of the smart cities concept. The work uses data from the Local Data Bank Polish Central Statistical Office (LDB). The author conducted a literature review of research papers related to smart cities and MCDM methods dated from 2010 to 2020. Based on calculations using the TOPSIS method, the results obtained that the city of Krakow has the highest value to become a smart city.
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Rigo, Paula Donaduzzi, Graciele Rediske, Carmen Brum Rosa, Natália Gava Gastaldo, Leandro Michels, Alvaro Luiz Neuenfeldt Júnior, and Julio Cezar Mairesse Siluk. "Renewable Energy Problems: Exploring the Methods to Support the Decision-Making Process." Sustainability 12, no. 23 (December 7, 2020): 10195. http://dx.doi.org/10.3390/su122310195.
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In the current scenario of increasing energy demand and encouraging sustainable development in countries, the energy sector’s planning has become more complex, involving multiple factors, such as technical, economic, environmental, social, and political. The decision process plays a vital role in structuring and evaluating complex decision situations related to the sector, considering various criteria and objectives, encouraging adopting policies to promote energy efficiency actions by increasing research on renewable energy sources and strategic energy decisions. The high number of multi-criteria decision support methods (MCDM) available and their efficiency in solving highly complex problems results in an impasse with their selection and application in specific decision situations. Thus, the scientific community requires methodological approaches that help the decision-maker select the method consistent with his problem. Accordingly, this paper conducts a Systematic Literature Review (SLR) of renewable energy problems associated with MCDM methods based on a final set of 163 articles. We identified five categories of problems solved by MCDM techniques: Source selection, location, sustainability, project performance, and technological performance. We separate the MCDM process into five evaluation steps (alternative selection, criteria selection, criteria weighting, evaluation of alternatives, and post-assessment analyzes), and we extract the methods used in each MCDM step from papers. This paper’s main contribution is identifying the most common MCDM methods in the renewable energy area and the energy problem they solve. Accordingly, this manuscript helps energy decision-makers, entrepreneurs, investors, and policy-makers to improve their ability to choose the proper MCDM methods to solve energy problems.
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Ozdemir, Sahika, and Yavuz Ozdemir. "Prioritizing store plan alternatives produced with shape grammar using multi-criteria decision-making techniques." Environment and Planning B: Urban Analytics and City Science 45, no. 4 (January 6, 2017): 751–71. http://dx.doi.org/10.1177/0265813516686566.
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To generate alternatives and variations of specific architectural models, shape grammars can be used by applying a set of geometric rules step by step. With the development in human life, advances in store design, design concept, commercial buildings’ architectural and spatial fiction, the magazine of the interior, and facade design cause rising competition between stores and also between designers. For this reason, in this paper we study the evaluation of store plan alternatives produced with shape grammar using two of multi-criteria decision-making (MCDM) techniques with fuzzy numbers, namely fuzzy analytic hierarchy process and fuzzy analytic network process. The main contribution of this paper is to prioritize plan alternatives using numerical methods with experts’ view. To the authors’ knowledge, this will be the first interdisciplinary study which uses MCDM techniques for evaluating shape grammar outputs in architectural design.
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Zyoud, Shaher H., and Daniela Fuchs-Hanusch. "Comparison of Several Decision-Making Techniques: A Case of Water Losses Management in Developing Countries." International Journal of Information Technology & Decision Making 18, no. 05 (September 2019): 1551–78. http://dx.doi.org/10.1142/s0219622019500275.
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Managing water losses in water supply systems has become a crucial concern. Multi criteria decision-making (MCDM) techniques are efficient in this regard. A framework of prioritizing strategies to manage water losses was tested by different MCDM techniques, Analytic Hierarchy Process (AHP) and several Fuzzy AHP techniques. The modified Fuzzy AHP produced the most credible and consistent outputs. Sensitivity analysis conducted over it showed that the ranking of strategies/alternatives was sensitive to changes in weights of criteria with higher importance. This analysis demonstrates the ability of AHP and Fuzzy AHP techniques to deal with complex issues in water loss management.
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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 (March 22, 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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Tian, Chao, and Juan Juan Peng. "A Multi-Criteria Decision-Making Method Based on the Improved Single-Valued Neutrosophic Weighted Geometric Operator." Mathematics 8, no. 7 (June 30, 2020): 1051. http://dx.doi.org/10.3390/math8071051.
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The aggregation operator is one of the most common techniques to solve multi-criteria decision-making (MCDM) problems. The aim of this paper is to propose an MCDM method based on the improved single-valued neutrosophic weighted geometric (ISVNWG) operator. First, the defects of several existing single-valued neutrosophic weighted geometric aggregation operators in terms of producing uncertain results in some special cases are analyzed. Second, an ISVNWG operator is proposed to avoid the defects of existing operators. Further, the properties of the proposed ISVNWG operator, including idempotency, boundedness, monotonicity, and commutativity, are discussed. Finally, a single-valued neutrosophic MCDM method based on the developed ISVNWG operator is proposed to overcome the defects of existing MCDM methods based on existing operators. Application examples demonstrate that our proposed operator and corresponding MCDM method are effective and rational for avoiding uncertain results in some special cases.
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Yap, Jeremy Yee Li, Chiung Chiung Ho, and Choo-Yee Ting. "A systematic review of the applications of multi-criteria decision-making methods in site selection problems." Built Environment Project and Asset Management 9, no. 4 (September 9, 2019): 548–63. http://dx.doi.org/10.1108/bepam-05-2018-0078.
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Purpose The purpose of this paper is to perform a systematic review on the application of different multi-criteria decision-making (MCDM) methods in solving the site selection problem across multiple problem domains. The domains are energy generation, logistics, public services and retail facilities. This study aims to answer the following research questions: Which evaluating criteria were used for each site selection problem domain? Which MCDM methods were frequently applied in a particular site selection problem domain? Design/methodology/approach The goals of the systematic review were to identify the evaluating criteria as well as the MCDM method used for each problem domain. A total of 81 recent papers (2014–2018) including 32 papers published in conference proceedings and 49 journal articles from various databases including IEEE Xplore, PubMed, Springer, Taylor and Francis as well as ScienceDirect were evaluated. Findings This study has shown that site selection for energy generation facilities is the most active site selection problem domain, and that the analytic hierarchy process (AHP) method is the most commonly used MCDM method for site selection. For energy generation, the criteria which were most used were geographical elements, land use, cost and environmental impact. For logistics, frequently used criteria were geographical elements and distance, while for public services population density, supply and demand, geographical layout and cost were the criteria most used. Criteria useful for retail facilities were the size (space) of the store, demographics of the site, the site characteristics and rental of the site (cost). Research limitations/implications This study is limited to reviewing papers which were published in the years 2014–2018 only, and only covers the domains of energy generation, logistics, public services and retail facilities. Practical implications MCDM is a viable tool to be used for solving the site selection problem across the domains of energy generation, logistics, public services and retail facilities. The usage of MCDM continues to be relevant as a complement to machine learning, even as data originating from embedded IoT devices in built environments becomes increasingly Big Data like. Originality/value Previous systematic review studies for MDCM and built environments have either focused on studying the MCDM techniques itself, or have focused on the application of MCDM for site selection in a single problem domain. In this study, a critical review of MCDM techniques used for site selection as well as the critical criteria used during the MCDM process of site selection was performed on four different built environment domains.
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Sen, Dilip Kumar, Saurav Datta, Saroj Kumar Patel, and Siba Sankar Mahapatra. "Multi-criteria decision making towards selection of industrial robot." Benchmarking: An International Journal 22, no. 3 (April 7, 2015): 465–87. http://dx.doi.org/10.1108/bij-05-2014-0046.
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Purpose – Robot selection is one of the critical decision-making tasks frequently performed by various industries in order to choose the best suited robot for specific industrial purposes. In recent marketplace, the number of robot manufacturers has increased remarkably offering a wide range of models and specifications; thus, robot selection has become indeed confusing as well as complicated task. Selection of an appropriate robot is a sensitive process; it may result massive letdown, if not chosen properly. Therefore, for unravel the selection problem; the purpose of this paper is to explore the preference ranking organization method for enrichment evaluation (PROMETHEE) II method. Design/methodology/approach – Apart from a large variety of robotic systems, existence of various multi-criteria decision making (MCDM) tools and techniques may create confusion to the decision makers’ in regards of application feasibility as well as superiority in performance to work under different decision-making situations. In this context, the PROMETHEE II method has been found as an efficient decision-making tool which provides complete ranking order of all available alternatives prudently, thus avoiding errors in decision making. Findings – In this context, the present paper highlights application potential of aforesaid PROMETHEE II method in relation to robot selection problem subjected to a set of quantitative (objective) evaluation data collected from the available literature resources. Advantages and disadvantages of PROMETHEE II method have also been reported in comparison to other existing MCDM approaches. Originality/value – The study bears significant managerial implications. Proper evaluation and selection of appropriate candidate robot would be helpful for the industries in order to improve product quality as well as to increase productivity. Proper utilization of resources could be ensured. Functioning would be accurate with reduced timespan. As a consequence, company can increase its profit margin in long run.
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Shinde, Dinesh, Hasan Öktem, Kanak Kalita, Shankar Chakraborty, and Xiao-Zhi Gao. "Optimization of Process Parameters for Friction Materials Using Multi-Criteria Decision Making: A Comparative Analysis." Processes 9, no. 9 (September 1, 2021): 1570. http://dx.doi.org/10.3390/pr9091570.
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Friction materials, mainly made of reinforced composites, should possess excellent physical and tribological properties, such as a higher coefficient of friction, minimum wear, adequate surface hardness, and higher porosity for various automotive brake applications. Attainment of those properties greatly depends on the settings of different input parameters, such as molding pressure, temperature and time, temperature and time of heat treatment/sintering, etc., during the processing of friction materials. In this article, four multi-criteria decision-making (MCDM) tools, i.e., technique for order of preference by similarity to ideal solution (TOPSIS), evaluation based on distance from average solution (EDAS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and multi-objective optimization on the basis of ratio analysis (MOORA) are applied to identify the optimal parametric combinations for two different friction materials. A comparative analysis of the derived results suggests the same optimal parametric mixes for all the MCDM techniques for both case studies. Thus, for the considered case studies, the optimal parametric combinations as molding time = 8 min, molding temperature = 175 °C, molding pressure = 27 MPa, sintering time = 10 h and sintering temperature = 225 °C, and molding pressure = 27.90 MPa, molding temperature = 170 °C, curing time = 8 min, and heat treatment time = 1 h, respectively, would help in attaining the most desired properties of friction materials. Improvements in the predicted response values prove the efficacy of the adopted MCDM techniques in determining the optimal combinations of various process parameters for friction materials.
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Chen, Shou Ming, and Miao Bu. "Evaluation the Environmental Awareness of Listed Companies by FAHP." Advanced Materials Research 790 (September 2013): 707–11. http://dx.doi.org/10.4028/www.scientific.net/amr.790.707.
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As an important component of corporate social responsibility, people pay more and more attention to enterprises environmental awareness, especially the listed company. Due to its multi-criteria nature, selecting a proper method involves an insight analysis among available multi-criteria decision making (MCDM) techniques. Among numerous methods of MCDM, this paper presents a decision framework based on fuzzy analytic hierarchy process (FAHP) for evaluating the environmental awareness of listed companies. The applicability of the proposed approach is verified through a case study.
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Aliyev, Rashad, Hasan Temizkan, and Rafig Aliyev. "Fuzzy Analytic Hierarchy Process-Based Multi-Criteria Decision Making for Universities Ranking." Symmetry 12, no. 8 (August 12, 2020): 1351. http://dx.doi.org/10.3390/sym12081351.
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High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students’ university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives’ evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities’ performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order.
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Le Xuan Hung, Trieu Quy Huy, Nguyen Van Cuong, Nguyen Manh Cuong, Luu Anh Tung, and Nguyen Thanh Tu. "Application of multi-criteria decision making technique in wire-cut EDM tool steel." Journal of Military Science and Technology, no. 83 (November 18, 2022): 103–9. http://dx.doi.org/10.54939/1859-1043.j.mst.83.2022.103-109.
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The findings of a study on the application of the MCDM technique to select the best input parameters in wire-cut electrical discharge machining (wire-cut EDM) 90CrSi tool steel are presented in this paper. The TOPSIS method was used in the study to solve the MCDM problem, and the Entropy method was used to compute the weights of the criteria. In this work, six input parameters including the cutting voltage VM, the pulse on time ton, the pulse off time toff, the servo voltage SV, the wire feed WF, the feed speed SPD, and the workpiece cutting radius R were investigated. Also, a 27-2 design experiment was performed and a total of 32 experimental runs were conducted. The MCDM problem was solved. According to the findings of this study, the best experimental setup is experiment No. 7 with the following input parameters: VM=9 (V), Ton=12 (s), Toff=13 (s), SV=25 (V), WF=8 (mm/min), SPD=4.5 (mm/min), and R=9 (mm).
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Melnik-Leroy, Gerda Ana, and Gintautas Dzemyda. "How to Influence the Results of MCDM?—Evidence of the Impact of Cognitive Biases." Mathematics 9, no. 2 (January 7, 2021): 121. http://dx.doi.org/10.3390/math9020121.
Full textAbstract:
Multi-criteria decision-making (MCDM) methods aim at dealing with certain limitations of human information processing. However, cognitive biases, which are discrepancies of human behavior from the behavior of perfectly rational agents, might persist even when MCDM methods are used. In this article, we focus on two among the most common biases—framing and loss aversion. We test whether these cognitive biases can influence in a predictable way both the criteria weights elicited using the Analytic Hierarchy Process (AHP) and the final ranking of alternatives obtained with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In a controlled experiment we presented two groups of participants with a multi-criteria problem and found that people make different decisions when presented with different but objectively equivalent descriptions (i.e., frames) of the same criteria. Specifically, the results show that framing and loss aversion influenced the responses of decision makers during pairwise comparisons, which in turn caused the rank reversal of criteria weights across groups and resulted in the choice of a different best alternative. We discuss our findings in light of Prospect Theory and show that the particular framing of criteria can influence the outcomes of MCDM in a predictable way. We outline implications for MCDM methodology and highlight possible debiasing techniques.
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Melnik-Leroy, Gerda Ana, and Gintautas Dzemyda. "How to Influence the Results of MCDM?—Evidence of the Impact of Cognitive Biases." Mathematics 9, no. 2 (January 7, 2021): 121. http://dx.doi.org/10.3390/math9020121.
Full textAbstract:
Multi-criteria decision-making (MCDM) methods aim at dealing with certain limitations of human information processing. However, cognitive biases, which are discrepancies of human behavior from the behavior of perfectly rational agents, might persist even when MCDM methods are used. In this article, we focus on two among the most common biases—framing and loss aversion. We test whether these cognitive biases can influence in a predictable way both the criteria weights elicited using the Analytic Hierarchy Process (AHP) and the final ranking of alternatives obtained with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). In a controlled experiment we presented two groups of participants with a multi-criteria problem and found that people make different decisions when presented with different but objectively equivalent descriptions (i.e., frames) of the same criteria. Specifically, the results show that framing and loss aversion influenced the responses of decision makers during pairwise comparisons, which in turn caused the rank reversal of criteria weights across groups and resulted in the choice of a different best alternative. We discuss our findings in light of Prospect Theory and show that the particular framing of criteria can influence the outcomes of MCDM in a predictable way. We outline implications for MCDM methodology and highlight possible debiasing techniques.
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Shanmugasundar, G., Gaurav Sapkota, Robert Čep, and Kanak Kalita. "Application of MEREC in Multi-Criteria Selection of Optimal Spray-Painting Robot." Processes 10, no. 6 (June 10, 2022): 1172. http://dx.doi.org/10.3390/pr10061172.
Full textAbstract:
Robots are being increasingly utilized for various operations in industrial and household applications. One such application is for spray painting, wherein atomized paint particles are sprayed on a surface to coat the surface with paint. As there are different models of robots available for the job, it becomes crucial to select the best among them. Multi-criteria decision-making (MCDM) techniques are widely used in various fields to tackle selection problems where there are many conflicting criteria and several alternatives. This work focuses on selecting the best robot among twelve alternatives based on seven criteria, among which payload, speed, and reach are beneficial criteria while mechanical weight, repeatability, cost, and power consumption are cost criteria. Five MCDM techniques, namely combination distance-based assessment (CODAS), complex proportional assessment (COPRAS), combined compromise solution (CoCoSo), multi-attributive border approximation area comparison (MABAC), and višekriterijumsko kompromisno rangiranje (VIKOR) were used for the selection while a weight calculation was performed using an objective weight calculation technique called MEREC. HY1010A-143 was found to be the most suitable robot for spray-painting applications by four of the five techniques used. Correlation studies showed a significant level of correlation among all the MCDM techniques.
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Sharma, Dheeraj P., Praveen Ranjan Srivastava, Ritanjali Panigrahi, Patanjal Kumar, and Smita Joshi. "A Multi-Criteria Decision Making Approach for ranking Business Schools." International Journal of Strategic Decision Sciences 10, no. 3 (July 2019): 33–56. http://dx.doi.org/10.4018/ijsds.2019070103.
Full textAbstract:
The proliferation of management institutes along with the establishment of new business school (B-School) has caused a dilemma among students while choosing the management institutes because of a plethora of options. To address the issue, this article provides a ranking framework which first identifies the criteria important for students while selecting a business school using NVivo software on the semi-structured survey. Further, the multi-criteria decision making (MCDM) technique ranks the business schools based on the selected criteria using fuzzy analytical hierarchy process (AHP) and evaluation based on distance from average solution (EDAS). The study has found that the ranking obtained is different from the National Institute Ranking Framework (NIRF) and other ranking systems for selecting a business school by students based on student-centered criteria. The rankings of business schools are obtained based on eight criteria: placement, location, infrastructure, industry-institute interaction, NIRF ranking, fee, innovativeness, and student-faculty ratio. The results of the study are validated using comparative analysis with different MCDM methods and sensitivity analysis with respect to change in weights of criteria. The theoretical and practical implications are discussed.