Статті в журналах: "Method of multicriteria classification"

1

Todeschini, R., and E. Marengo. "Linear discriminant classification tree: A user-driven multicriteria classification method." Chemometrics and Intelligent Laboratory Systems 16, no. 1 (September 1992): 25–35. http://dx.doi.org/10.1016/0169-7439(92)80075-f.

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Silva, Maisa M., Ana Paula H. de Gusmão, and Ana Paula C. S. Costa. "An Outranking Multicriteria Method for Nominal Classification Problems with Minimum Performance Profiles." Mathematical Problems in Engineering 2019 (May 5, 2019): 1–14. http://dx.doi.org/10.1155/2019/4078909.

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In recent years, nominal classification problems have gained importance, especially in the context of strategic management of organizations. In this sense, this paper presents a novel multicriteria nominal classification method, derived from the concepts of PROMETHEE, applied to use in problems characterized by minimum performance profiles (MMP) for the classes. The main advantages of this proposal are criterion and alternative flexibility for classes; robustness, because it uses the concepts of a well-known method (PROMETHEE); and usefulness, because many real situations are characterized by MMP for the classes. Moreover, a real-world example is presented: a retailer’s assignment in a bank, showing the applicability of the method. The proposal of a new multicriteria nominal classification method emerges from a need to devise a more flexible and realistic procedure for characterizing classes because the feature of criterion and alternative flexibility for classes has not been addressed in any extant multicriteria nominal classification procedure. The present proposal thereby endeavors to address this deficit in the multicriteria field.

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Belacel, Nabil, Hiral Bhasker Raval, and Abraham P. Punnen. "Learning multicriteria fuzzy classification method PROAFTN from data." Computers & Operations Research 34, no. 7 (July 2007): 1885–98. http://dx.doi.org/10.1016/j.cor.2005.07.019.

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4

Liang, Liang, Ren Yan Jiang, and Yin Liang. "A Multicriteria Decision Method with Uncertain Information in Financial Credit Loan Decision-Making." Applied Mechanics and Materials 52-54 (March 2011): 1868–72. http://dx.doi.org/10.4028/www.scientific.net/amm.52-54.1868.

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It is difficult to obtain the correct criteria weights with uncertain information in the multicriteria decision-making. Many methods depend on the subjective estimate. Therefore, a method is presented to evaluate the samples ranking only need the importance order of criteria. It evaluates firstly the overall ranking scores of samples based on the graphical classification and multicriteria hierarchical integrated methods. Subsequently, the relation model between the criteria scores and overall ranking scores of samples is built by linear regression. Finally, a fincial credit loan decision-making problem is presented to describe the way of the multicriteria decisiion making process. The analysis to compare with the AHP method illustrates the proposed method is objective and effective.

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Khoder, Mahdi, Serge Kashana, Jihan Khoder, and Rafic Younes. "Multicriteria classification method for dimensionality reduction adapted to hyperspectral images." Journal of Applied Remote Sensing 11, no. 2 (April 6, 2017): 025001. http://dx.doi.org/10.1117/1.jrs.11.025001.

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6

Wang, Xiao-yi, Yi Yang, Yu-ting Bai, Jia-bin Yu, Zhi-yao Zhao, and Xue-bo Jin. "Fuzzy Boost Classifier of Decision Experts for Multicriteria Group Decision-Making." Complexity 2020 (August 17, 2020): 1–10. http://dx.doi.org/10.1155/2020/8147617.

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The expert is a vital role in multicriteria decision-making, which provides source decision opinions. In the existing group decision-making activities, the selection of experts is usually conducted artificially, which relies on personal subjective experience. It has been the urgent demand for an automatic selection of experts, which can help to determine their weights for the follow-up decision calculation. In this paper, an expert classification method is proposed to solve the problem. First, the CatBoost classification algorithm is improved by integrating the 2-tuple linguistic, which can effectively extract the features of samples. Second, the framework of the expert classification is designed. The flow combines the expert resume collection, expert classification, and database update. Third, a decision-making case is analyzed for the expert selection issue. The experiment and result indicate that the proposed classifier performs better than the classic methods. The proposed classification method of the decision experts can support the automatic and intelligent operation of the decision-making activities.

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7

Zopounidis, Constantin, and Michael Doumpos. "Multicriteria classification and sorting methods: A literature review." European Journal of Operational Research 138, no. 2 (April 2002): 229–46. http://dx.doi.org/10.1016/s0377-2217(01)00243-0.

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Kefer, Petar, Dragan D. Milanovic, Mirjana Misita, and Aleksandar Zunjic. "Fuzzy Multicriteria ABC Supplier Classification in Global Supply Chain." Mathematical Problems in Engineering 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/9139483.

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The determination of the optimal purchasing strategy in enterprise that is a part of global supply chain could be performed in two steps. In step one, a classification of potential suppliers is performed in order to determine the optimal portfolio of suppliers. This is delivered by using the fuzzy multicriteria proposed ABC classification method. Uncertainties in relative importance of criteria and their values are described by linguistic expressions. Modelling of linguistic expressions is based on the fuzzy sets theory. In the second step, ranking of optimal portfolio of suppliers is performed by using the modified ELECTRE method. The obtained results represent valuable input for determining the long time purchasing strategy and building partnership with the best suppliers. The developed two-step model is verified on real life data. The obtained results indicate good compliance with the opinions management in this type of industry. It is worth to mention that the proposed model can be easily extended and adopted to the analysis of other issues of management which could be applicable in different research areas.

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Costa, Ana Sara, Salvatore Corrente, Salvatore Greco, José Rui Figueira, and José Borbinha. "A robust hierarchical nominal multicriteria classification method based on similarity and dissimilarity." European Journal of Operational Research 286, no. 3 (November 2020): 986–1001. http://dx.doi.org/10.1016/j.ejor.2020.04.021.

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Salukvadze, M., N. Jibladze, V. Maisuradze, and A. Topchishvili. "Methods and algorithms for solving multicriteria problems – classification approach." Model Assisted Statistics and Applications 2, no. 4 (January 11, 2008): 239–51. http://dx.doi.org/10.3233/mas-2007-2406.

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11

Liu, Fan, and Ning Ma. "Multicriteria ABC Inventory Classification Using the Social Choice Theory." Sustainability 12, no. 1 (December 24, 2019): 182. http://dx.doi.org/10.3390/su12010182.

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The multicriteria ABC inventory classification has been widely adopted by organizations for the purpose of specifying, monitoring, and controlling inventory efficiently. It categorizes the items into three groups based on some certain criteria, such as inventory cost, part criticality, lead time, and commonality. There has been extensive research on such a problem, but few have considered that the judgments about criteria’s importance order usually exhibit a substantial degree of variability. In light of this, we propose a new methodology for handling the multicriteria ABC inventory classification problem using the social choice theory. Specifically, the pessimistic and optimistic results for all possible individual judgments are obtained in a closed-form manner, which are then balanced by the Hurwicz criterion with a “coefficient of optimism”. The CRITIC (Criteria Importance Through Intercriteria Correlation) method is used to aggregate the individual judgments into a collective choice, according to which the items are classified into Groups A, B, and C. Through a numerical experiment, we show that the proposed methodology not only considers all possible preferences among the criteria, but also generates flexible classification schemes.

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Iqbal, Qamar, Don Malzahn, and Lawrence E. Whitman. "Selecting a Multicriteria Inventory Classification Model to Improve Customer Order Fill Rate." Advances in Decision Sciences 2017 (April 5, 2017): 1–11. http://dx.doi.org/10.1155/2017/5028919.

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Multicriteria models have been proposed for inventory classification in previous studies. However, it is important to make a decision when a particular multicriteria inventory classification model should be preferred over other models and also if the highest performing model remains the highest performing at all times. Companies always look for ways to improve customer order fulfillment process. This paper shows how better inventory classification can improve customer order fill rate in variable settings. The method to compare the inventory classification models with regard to improving customer order fill rate is proposed. The cut-off point is calculated which indicates when a model currently in use should be dropped in favor of another model to increase revenue by filling more orders. Sensitivity analysis is also performed to determine how holding cost and demand uncertainty affect the performance metric. Finally, regression analysis and hypothesis testing inform the decision-maker of how a model’s performance differs from other models at various values of holding cost and standard deviation of demand.

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Sepulveda, Juan M., and Ivan S. Derpich. "Multicriteria Supplier Classification for DSS: Comparative Analysis of Two Methods." International Journal of Computers Communications & Control 10, no. 2 (April 1, 2015): 238. http://dx.doi.org/10.15837/ijccc.2015.2.1755.

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14

Perić, Tunjo, and Željko Mandić. "MULTI-CRITERIA PROGRAMMING METHODS AND PRODUCTION PLAN OPTIMIZATION PROBLEM SOLVING IN METAL INDUSTRY." Journal Human Research in Rehabilitation 7, no. 2 (September 2017): 59–66. http://dx.doi.org/10.21554/hrr.091707.

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This paper presents the production plan optimization in the metal industry considered as a multi-criteria programming problem. We first provided the definition of the multi-criteria programming problem and classification of the multicriteria programming methods. Then we applied two multi-criteria programming methods (the STEM method and the PROMETHEE method) in solving a problem of multi-criteria optimization production plan in a company from the metal industry. The obtained results indicate a high efficiency of the applied methods in solving the problem.

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15

Ulucan, Aydin, and Kazim Baris Atici. "A MULTIPLE CRITERIA SORTING METHODOLOGY WITH MULTIPLE CLASSIFI CATION CRITERIA AND AN APPLICATION TO COUNTRY RISK EVALUATION." Technological and Economic Development of Economy 19, no. 1 (April 2, 2013): 93–124. http://dx.doi.org/10.3846/20294913.2012.763070.

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In this paper, we propose an extension of the standard UTADIS methodology, an approach that originates from multicriteria decision aid (MCDA) for sorting problems, such that it can handle more than one classification criteria simultaneously which possibly involves different predefined classes for alternatives. Moreover, we test the classification ability of the standard UTADIS methodology using the out-of-classification criterion approach, a new variant of the studies comprising out-of-time and out-of-sample testing methodologies. Results obtained in out-of-classification criterion testing are then compared with the classification ability of the Multiple Classification Criteria UTADIS (MCC UTADIS). Finally, an application to country risk evaluation is performed. In this application, classifications of two credit rating agencies, Standard & Poor's and Moody's, are taken as two different classification criteria. Moreover, robustness of MCC UTADIS method is tested through using several data sets. Results indicate that MCC UTADIS involving more than one classification criteria performs very close to standard UTADIS with single classification criterion and performs better than the out-of-classification criterion tests. These results emphasize both the sensitivity of UTADIS models to the classification criteria and the importance of using a multiple classification criteria approach.

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Kaabi, Hadhami, Khaled Jabeur, and Talel Ladhari. "A Genetic Algorithm-Based Classification Approach for Multicriteria ABC Analysis." International Journal of Information Technology & Decision Making 17, no. 06 (November 2018): 1805–37. http://dx.doi.org/10.1142/s0219622018500475.

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ABC analysis is a widespread classification technique designed to manage inventory items in an effective way by relaxing controls on low valued items and applying more rigorous controls on high valued items. In the literature, many classification models issued from different methodologies such as Mathematical Programming (MP), Metaheuristics, Artificial Intelligence (AI) and Multicriteria Decision Making (MCDM) are proposed to perform the ABC inventory classification. To the best of our knowledge, the cross-fertilization of classification models issued from different methodologies is rarely tackled in the literature. This paper proposes some hybrid classification models based on both Genetic Algorithm (Metaheuristics) and two MCDM methods (Weighted Sum (WS) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)) to carry out the ABC inventory classification. To test the performance of the proposed classification models with respect to some existing models, a benchmark dataset from a Hospital Respiratory Therapy Unit (HRTU) is used. The computational results show that our proposed models outperformed the existing classification models according to some inventory performance measures. An additional performance analysis has also shown the effectiveness of our proposed models in inventory management.

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Kochkarov, Rasul. "Multicriteria Optimization Problem on Prefractal Graph." Mathematics 10, no. 6 (March 14, 2022): 930. http://dx.doi.org/10.3390/math10060930.

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Even among single-criteria discrete problems, there are NP-hard ones. Multicriteria problems on graphs in many cases become intractable. Currently, priority is given to the study of applied multicriteria problems with specific criteria; there is no classification of criteria according to their type and content. There are few studies with fuzzy criteria, both weight and topological. Little attention is paid to the stability of solutions, and this is necessary when modeling real processes due to their dynamism. It is also necessary to study the behavior of solution sets for various general and individual problems. The theory of multicriteria optimization is a rather young branch of science and requires the development of not only particular methods, but also the construction of a methodological basis. This is also true in terms of discrete graph-theoretic optimization. In this paper, we propose to get acquainted with multicriteria problems for a special class of prefractal graphs. Modeling natural objects or processes using graphs often involves weighting edges with many numbers. The author proposes a general formulation of a multicriteria problem on a multi-weighted prefractal graph; defines three sets of alternatives—Pareto, complete and lexicographic; and proposes a classification of individual problems according to the set of feasible solutions. As an example, we consider an individual problem of placing a multiple center with two types of weight criteria and two types of topological ones. An algorithm with estimates of all criteria of the problem is proposed.

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Hu, Yi-Chung, and Hsiao-Chi Chen. "Integrating multicriteria PROMETHEE II method into a single-layer perceptron for two-class pattern classification." Neural Computing and Applications 20, no. 8 (July 14, 2010): 1263–71. http://dx.doi.org/10.1007/s00521-010-0424-2.

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19

Hatefi, S. M., and S. A. Torabi. "A Common Weight Linear Optimization Approach for Multicriteria ABC Inventory Classification." Advances in Decision Sciences 2015 (January 1, 2015): 1–11. http://dx.doi.org/10.1155/2015/645746.

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Organizations typically employ the ABC inventory classification technique to have an efficient control on a huge amount of inventory items. The ABC inventory classification problem is classification of a large amount of items into three groups: A, very important; B, moderately important; and C, relatively unimportant. The traditional ABC classification only accounts for one criterion, namely, the annual dollar usage of the items. But, there are other important criteria in real world which strongly affect the ABC classification. This paper proposes a novel methodology based on a common weight linear optimization model to solve the multiple criteria inventory classification problem. The proposed methodology enables the classification of inventory items via a set of common weights which is very essential in a fair classification. It has a remarkable computational saving when compared with the existing approaches and at the same time it needs no subjective information. Furthermore, it is easy enough to apply for managers. The proposed model is applied on an illustrative example and a case study taken from the literature. Both numerical results and qualitative comparisons with the existing methods reveal several merits of the proposed approach for ABC analysis.

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Lipshitz, G., and B. H. Massam. "Classification of Development Towns in Israel by Using Multicriteria Decision Aid Techniques." Environment and Planning A: Economy and Space 30, no. 7 (July 1998): 1279–94. http://dx.doi.org/10.1068/a301279.

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In research on regional development little attention is devoted to socioeconomic distinctions within peripheral and core regions, rather than disparities between regions. This approach is evidently shared by policymakers, who tend to formulate regional development policies without taking account of existing socioeconomic differences within the regions. Development policy for Israel's national peripheries is a salient example of a homogeneous development policy. The findings of the present study point to the need to reconsider regional development by placing the main emphasis on the fashioning of a differential regional development policy, together with or in preference to a homogeneous or uniform policy. The findings are obtained through application of a relatively new method of multivariate analysis: ‘multicriteria decision aid’ (MCDA). The study suggests theoretical and methodological considerations in the larger context of regional development.

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Tarapata, Zbigniew. "Selected Multicriteria Shortest Path Problems: An Analysis of Complexity, Models and Adaptation of Standard Algorithms." International Journal of Applied Mathematics and Computer Science 17, no. 2 (June 1, 2007): 269–87. http://dx.doi.org/10.2478/v10006-007-0023-2.

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Selected Multicriteria Shortest Path Problems: An Analysis of Complexity, Models and Adaptation of Standard AlgorithmsThe paper presents selected multicriteria (multiobjective) approaches to shortest path problems. A classification of multi-objective shortest path (MOSP) problems is given. Different models of MOSP problems are discussed in detail. Methods of solving the formulated optimization problems are presented. An analysis of the complexity of the presented methods and ways of adapting of classical algorithms for solving multiobjective shortest path problems are described. A comparison of the effectiveness of solving selected MOSP problems defined as mathematical programming problems (using the CPLEX 7.0 solver) and multi-weighted graph problems (using modified Dijkstra's algorithm) is given. Experimental results of using the presented methods for multicriteria path selection in a terrain-based grid network are given.

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Diti, Irene, Daniele Torreggiani, and Patrizia Tassinari. "Rural landscape and cultural routes: a multicriteria spatial classification method tested on an Italian case study." Journal of Agricultural Engineering 46, no. 1 (April 21, 2015): 23. http://dx.doi.org/10.4081/jae.2015.451.

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Europe is characterised by a rich net of itineraries that during the Middle Ages were taken by pilgrims head toward the holy places of Christianity. In Italy the main pilgrimage route is the Via Francigena (the road that comes from France), which starts from Canterbury and arrives in Rome, running through Europe for about 1800 km. Municipalities and local associations are focused on purposes and actions aimed at the promotion of those routes, rich in history and spirituality. Also for the European Union the enhancement of those itineraries, nowadays used both by pilgrims and tourists, is crucial, as shown by the various projects aimed at the identification of tools for the development of sustainable cultural tourism. It is important to understand how landscape, that according to the European Landscape Convention reflects the sense of places and represents the image of their history, has evolved along those roads, and to analyse the relationships between the built and natural environments, since they maintain a remarkable symbolic connection between places and peoples over time and history. This study focuses on the Italian section of the Via Francigena that crosses the Emilia-Romagna region, in the province of Piacenza. A land classification method is proposed, with the aim to take into account different indicators: land zoning provided by regional laws, elements of relevant historical and natural value, urban elements, type of agriculture. The analyses are carried out on suitable buffers around the path, thus allowing to create landscape profiles. As nature is a key element for the spirituality character of these pilgrimage routes, the classification process takes into account both protected and other valuable natural elements, besides agricultural activities. The outcomes can be useful to define tools aimed to help pilgrims and tourists to understand the surrounding places along their walk, as well as to lend support to rural and urban planning and integrated local development and landscape enhancement projects.

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Johnson, Sindhu R., Raymond P. Naden, Jaap Fransen, Frank van den Hoogen, Janet E. Pope, Murray Baron, Alan Tyndall, et al. "Multicriteria decision analysis methods with 1000Minds for developing systemic sclerosis classification criteria." Journal of Clinical Epidemiology 67, no. 6 (June 2014): 706–14. http://dx.doi.org/10.1016/j.jclinepi.2013.12.009.

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24

Henrique dos Santos, Hugo, Vitor Natã Marques, and Luiz Felipe Ferreira Paschoali. "The analysis of barriers for implementing circular economy practices using the Analytic Hierarchy Process (AHP)." Revista Gestão da Produção Operações e Sistemas 16, no. 03 (September 23, 2021): 99–118. http://dx.doi.org/10.15675/gepros.v16i3.2793.

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Purpose – This paper aims to identify and classify the main barriers for adopting circular economy practices using the Analytic Hierarchy Process (AHP) method for prioritization. The proposed methodology evaluates the importance of different classes of barriers for adopting circular economy practices in a food company and metalworking company. Theoretical framework – This study was based on the current theory of barriers to adopt circular economy practices and multicriteria decision-making. Design/methodology/approach – The Analytic Hierarchy Process (AHP) method was used to assess and prioritize barriers for circular economy practices. Stability was ranked using a sensitivity analysis. Findings – The results indicate significant differences in the classification of barriers. While the food manufacturing company indicate that the main barriers are related to technical information, the metalworking company considered that barriers relating to financial and economic issues have more of an impact. Originality/value – The study contributes to providing insights so that managers have a greater perception of the main difficulties in adopting circular economy practices, in addition, the study also contributes to extending the application of multicriteria decision making methodologies to the circular economy and evaluating the relative importance of the barriers. Keywords - Circular Economy; Analytic Hierarchy Process; multicriteria analysis; barriers; sustainable development.

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Ustinovičius, Leonas, and Dmitry Kochin. "VERBAL ANALYSIS OF THE INVESTMENT RISK IN CONSTRUCTION." Journal of Business Economics and Management 4, no. 4 (December 31, 2003): 228–34. http://dx.doi.org/10.3846/16111699.2003.9636060.

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Obtaining of reliable enough estimations of investment quality is a complex task, since there is no universal indicator of capital recovery probability. Classification is a very important aspect in decision making. This means the prescription of projects to the particular classes. Very often it is stated that classes in decision making are determined by the particular parameters, i.e. the efficiency of technical and technological decisions, credit value determination of the project, etc. This article presents a verbal method of determining investment risk in construction. The problem under consideration is investment assessment depending on the risk level. Formally the problem is stated as multicriteria classification one. A hierarchical approach to considered effectiveness indicators is proposed. The proof of effectiveness of the method is presented. A procedure of method application is described for a practical task.

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Ameljańczyk, Andrzej, and Maciej Kiedrowicz. "Multicriteria methods for identifying patterns in the analysis of the flow of “dangerous financial documents”." MATEC Web of Conferences 210 (2018): 04010. http://dx.doi.org/10.1051/matecconf/201821004010.

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The article outlines a concept of applying the methodology for identifying patterns used for detecting documents suggesting the execution of some criminal financial transactions. The analogies of diagnostic processes for disease classification in medicine were used in the method. The idea of the described method consists in defining model patterns of financial documents, suggesting criminal activity in the form of the financial flow and developing mathematical models of actual financial documents which shall be used for the comparisons with the patterns at a later stage of the process. The next step is to develop similarity indicators of documents to appropriate patterns, to define and develop a multicriteria detection area for the documents and to develop a method for dividing the set of monitored documents into similar document classes. The final stage is the development of multicriteria rankings that allow to organize the set of transaction documents according to the degree of similarity to the relevant patterns and to determine the optimal cut-off threshold in the ranking of documents intended for a more detailed analysis. The described method may be used in counteracting financial crimes, and in particular in combating money laundering.

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Li, Hong, Guo Yin Wang, Guang Lei Gou, and Wen Liu. "Boundary Variable Precision Dominance-Based Rough Set Approach in Multicriteria Sorting Problems." Advanced Materials Research 734-737 (August 2013): 3102–6. http://dx.doi.org/10.4028/www.scientific.net/amr.734-737.3102.

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This paper provides a novel method of boundary variable precision dominance-based rough set approach (BVP-DRSA) to solve multicriteria sorting problem that differs from usual classification problems since it takes into account preference orders in the description of objects by condition and decision attributes. The major contribution of our BVP-DRSA method is that it combines variable precision and dominance-based rough set approach (DRSA). This approach is different from the dominance-based rough set approach (DRSA) because it takes boundary into account and can deal with boundary directly. Comparative experiments form datasets of UCI and empirical results shows that our BVP-DRSA is far more efficient than directly using already known classing algorithms and DRSA.

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Lee, Kuo-Liang, and Shu-Chen Lin. "An empirical study on assessing optimal type of distribution park: Applying fuzzy multicriteria Q-analysis method." Yugoslav Journal of Operations Research 22, no. 1 (2012): 79–96. http://dx.doi.org/10.2298/yjor101212001l.

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In this paper, through an empirical study it is explored how respondents viewed suitable modes on locations for developing a distribution park. A fuzzy multiple criteria Q-analysis (MCQA) method is used to empirically evaluate location development for suitable types of international distribution park. The fuzzy MCQA method integrates MCQA, a fuzzy measure method and a fuzzy grade classification method. This improves the constraints evaluated by decision-makers, resulting in an explicit result value for each criterion to be evaluated, greatly decreasing the complexity of the evaluation process and preserving the advantages of the traditional MCQA method.

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Doumpos, M., Y. Marinakis, M. Marinaki, and C. Zopounidis. "An evolutionary approach to construction of outranking models for multicriteria classification: The case of the ELECTRE TRI method." European Journal of Operational Research 199, no. 2 (December 2009): 496–505. http://dx.doi.org/10.1016/j.ejor.2008.11.035.

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30

Mehea, Marek, Slavomíra Staaková, Adela Feranecová, and Veronika Ragániová. "Selecting the savings account in the Slovak Republic." Problems and Perspectives in Management 14, no. 4 (December 14, 2016): 8–16. http://dx.doi.org/10.21511/ppm.14(4).2016.01.

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There are currently many investment and financial products that can be used for capitalizing of savings. Although investments in various commodities, shares, securities, or funds can be with high yields, it requires some knowledge and experience. Unattempted investor may experience unpleasant surprise of possible losses of greater amount of money, as such investments are generally associated with a higher risk. For these reasons, the majority of the population remains in the Slovak Republic faithful to traditional forms of capitalizing of funds. One of these forms are savings accounts in banks. The main purpose of this paper is to find possibly the best savings account in the Slovak Republic. In cooperation with experts from the field of banking, the authors have defined the selection criteria of savings accounts, assessed their importance and, then, they have arranged savings accounts offered in the Slovak Republic according to achieved score. For this purpose, methods of multicriteria decision making were used. These methods are based on the evaluation of several alternative solutions based on multiple criteria. These criteria must be assigned by weights which represent their importance in decision making process. These weights were calculated using the Saaty’s method, which is a method based on mutual comparison of all the criteria. For final ranking of term deposits, taking into account the weights of the criteria, the method TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) was used. Keywords: savings, banking products, savings accounts, multicriteria decision making. JEL Classification: E21, G21

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Jurišić, Mladen, Ivan Plaščak, Oleg Antonić, and Dorijan Radočaj. "Suitability Calculation for Red Spicy Pepper Cultivation (Capsicum annum L.) Using Hybrid GIS-Based Multicriteria Analysis." Agronomy 10, no. 1 (December 18, 2019): 3. http://dx.doi.org/10.3390/agronomy10010003.

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Red spicy pepper is traditionally considered as the fundamental ingredient for multiple authentic products of Eastern Croatia. The objectives of this study were to: (1) evaluate the optimal interpolation method necessary for modeling of criteria layers; (2) calculate the sustainability and vulnerability of red spicy pepper cultivation using hybrid Geographic Information System (GIS)-based multicriteria analysis with the analytical hierarchy process (AHP) method; (3) determine the suitability classes for red spicy pepper cultivation using K-means unsupervised classification. The inverse distance weighted interpolation method was selected as optimal as it produced higher accuracies than ordinary kriging and natural neighbour. Sustainability and vulnerability represented the positive and negative influences on red spicy pepper production. These values served as the input in the K-means unsupervised classification of four classes. Classes were ranked by the average of mean class sustainability and vulnerability values. Top two ranked classes, highest suitability and moderate-high suitability, produced suitability values of 3.618 and 3.477 out of a possible 4.000, respectively. These classes were considered as the most suitable for red spicy pepper cultivation, covering an area of 2167.5 ha (6.9% of the total study area). A suitability map for red spicy pepper cultivation was created as a basis for the establishment of red spicy pepper plantations.

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Deng, Weibin, Changlin Xu, Jin Liu, and Feng Hu. "A Novel Distance between Vague Sets and Its Applications in Decision Making." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/281095.

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A novel distance between vague sets (VSs) is presented after the inadequacies of existing distance measures between vague sets are analyzed by artificial vague sets. The proposed method investigates the assignment of degree of hesitation to the membership and nonmembership degree, and the properties are also discussed. The performances of the new method are illustrated by pattern classification problem. Finally, the proposed method is applied into multicriteria fuzzy decision making, where the linear programming method is taken to generate optimal weights for every criterion and the best alternative is obtained by the weighted sum of distance measures between each alternative and the idea alternative with respect to a set of criteria. The experimental results show the effectiveness of the proposed method.

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Hoang, Lich, Cao Tan, Le My, and Dung Nguyen. "Taxation and economic growth: A regression analysis based on a new classification." Ekonomski horizonti 23, no. 3 (2021): 215–29. http://dx.doi.org/10.5937/ekonhor2103225h.

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This paper examines the impact of taxes on the economic growth based on classifying countries by GDP per capita and a tax burden. The Partitioning Around Medoids (PAM) technique is used because it is not too sensitive to outliers. Through this multicriteria classification technique, the Generalized Method of Moments (GMM) is employed to analyze the data of the three groups consisting of 63 countries from 2003 to 2017. The results show that most taxes have a positive impact on economic growth in poor countries (Group 1). Interestingly, taxes on goods and services promote economic growth in rich countries (Group 3), rather than having a negative effect, as is concluded by some previous studies. Specially, while the property tax has a negative effect on economic growth in rich countries, its impact is significantly positive in poor countries.

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PENG, YI, GANG KOU, GUOXUN WANG, WENSHUAI WU, and YONG SHI. "ENSEMBLE OF SOFTWARE DEFECT PREDICTORS: AN AHP-BASED EVALUATION METHOD." International Journal of Information Technology & Decision Making 10, no. 01 (January 2011): 187–206. http://dx.doi.org/10.1142/s0219622011004282.

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Classification algorithms that help to identify software defects or faults play a crucial role in software risk management. Experimental results have shown that ensemble of classifiers are often more accurate and robust to the effects of noisy data, and achieve lower average error rate than any of the constituent classifiers. However, inconsistencies exist in different studies and the performances of learning algorithms may vary using different performance measures and under different circumstances. Therefore, more research is needed to evaluate the performance of ensemble algorithms in software defect prediction. The goal of this paper is to assess the quality of ensemble methods in software defect prediction with the analytic hierarchy process (AHP), which is a multicriteria decision-making approach that prioritizes decision alternatives based on pairwise comparisons. Through the application of the AHP, this study compares experimentally the performance of several popular ensemble methods using 13 different performance metrics over 10 public-domain software defect datasets from the NASA Metrics Data Program (MDP) repository. The results indicate that ensemble methods can improve the classification results of software defect prediction in general and AdaBoost gives the best results. In addition, tree and rule based classifiers perform better in software defect prediction than other types of classifiers included in the experiment. In terms of single classifier, K-nearest-neighbor, C4.5, and Naïve Bayes tree ranked higher than other classifiers.

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RIGOPOULOS, GEORGE, and KOSTAS ANAGNOSTOPOULOS. "FUZZY MULTICRITERIA ASSIGNMENT FOR NOMINAL CLASSIFICATION: METHODOLOGY AND APPLICATION IN EVALUATION OF GREEK BANK'S ELECTRONIC PAYMENT RETAILERS." International Journal of Information Technology & Decision Making 09, no. 03 (May 2010): 437–54. http://dx.doi.org/10.1142/s0219622010003890.

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This paper presents a novel multicriteria procedure for nominal classification problems. Assignment of an action to a category is based on the comparison between action and category's least typical representative, which is considered as the category inclusion threshold. Evaluation is executed considering performance on evaluation criteria and calculation of a fuzzy inclusion relation for every action, generalizing preference relations model with concordance and nondiscordance concepts as used in ELECTRE methods. An application to a classification problem in banking is also presented in order to demonstrate its applicability to similar problems.

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Fernandes, Ciro Henrique de Araújo, Lucio Camara e. Silva, Patricia Guarnieri, and Bárbara de Oliveira Vieira. "Multicriteria Model Proposition to Support the Management of Systems of E-Waste Collection." Logistics 5, no. 3 (September 3, 2021): 60. http://dx.doi.org/10.3390/logistics5030060.

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Background: Considering the global concern in balancing economic growth with environmental sustainability, the study proposes a model to support multicriteria decision-making. From the systematic literature review and bibliometric analysis, there was an increasing trend in studies on electronic waste due to governments, stakeholders, and the population to better address the management of this waste; Methods: We propose a decision model considering some aspects and phases that help from collecting information to support decision making, based on the FITradeoff ordering method, to support policy decisions for managing Waste from Electrical and Electronic Equipment (WEEE) collection systems.; Results: After applying the proposed model, validated based on the perception of a decision-maker working in a federal public agency, we obtained the final classification with ten positions of alternatives; Conclusions: This outcome can assist in decision making and management of the collection of WEEE. In addition, we made recommendations to manufacturers have more responsibility in the design and traceability of the product to guarantee its recovery after disposal effectively.

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Figueiredo, Ciro José Jardim de, and Caroline Maria de Miranda Mota. "A Classification Model to Evaluate the Security Level in a City Based on GIS-MCDA." Mathematical Problems in Engineering 2016 (2016): 1–10. http://dx.doi.org/10.1155/2016/3534824.

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The aim of this paper is to map the most favorable locations for the occurrence of robberies in the Brazilian city through the multicriteria method Dominance-Based Rough Set Approach. Considering the city divisions with alternatives and evaluating by several spatial criteria, a decision-maker is building a preference model with based previous knowledge. Next, decision rules induced from preference information are introduced to the spatial environment to get the results. The decision rules can be seen as conditional part (represented by criteria) and decision part (assignment to decision classes). The rules classify all the alternatives according to security level. Moreover, the rules help to understand the social dynamics of the city and to assist in the proposition of strategies against violence.

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Atiqah Rochin Demong, Nur, Jie Lu, and Farookh Khadeer Hussain. "An Adaptive Personalized Property Investment Risk Analysis Method Based on Data-Driven Approach." International Journal of Information Technology & Decision Making 20, no. 02 (February 26, 2021): 671–706. http://dx.doi.org/10.1142/s0219622021500115.

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Risk assessment analysis for investment decisions largely depends on expert judgment using traditional approaches and is lacking in considering investors’ different preferences and limitations. This paper proposes an adaptive personalized property investment risk analysis (APPIRA) method to identify the property investment determinants using a data-driven and personalized approach to weight the risk factors using the multicriteria decision model for optimal solutions. Result for predictive modeling using value prediction technique that measures the median house price depicts that the best method used was nonseasonal ARIMA. Furthermore, classification technique indicates that in each of the three selected suburbs, different property characteristics determined the rental properties desirable. As shown in result, for the investors who plan to invest in property for rental purposes, they need to choose townhouse type or property to make it rentable while for Vaucluse, terrace houses. These results can be applied into practice and will benefit the property industry directly.

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Carnero, María Carmen. "Waste Segregation FMEA Model Integrating Intuitionistic Fuzzy Set and the PAPRIKA Method." Mathematics 8, no. 8 (August 17, 2020): 1375. http://dx.doi.org/10.3390/math8081375.

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Segregation is an important step in health care waste management. If done incorrectly, the risk of preventable infections, toxic effects, and injuries to care and non-care staff, waste handlers, patients, visitors, and the community at large, is increased. It also increases the risk of environmental pollution and prevents recyclable waste from being recovered. Despite its importance, it is acknowledged that poor waste segregation occurs in most health care organizations. This study therefore intends to produce, for the first time, a classification of failure modes related to segregation in the Nuclear Medicine Department of a health care organization. This will be done using Failure Mode and Effects Analysis (FMEA), by combining an intuitionistic fuzzy hybrid weighted Euclidean distance operator, and the multicriteria method Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA). Subjective and objective weights of risk factors were considered simultaneously. The failure modes identified in the top three positions are: improper storage of waste (placing items in the wrong bins), improper labeling of containers, and bad waste management (inappropriate collection periods and bin set-up).

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Alamanos, Angelos, Nikitas Mylopoulos, Athanasios Loukas, and Dimitrios Gaitanaros. "An Integrated Multicriteria Analysis Tool for Evaluating Water Resource Management Strategies." Water 10, no. 12 (December 7, 2018): 1795. http://dx.doi.org/10.3390/w10121795.

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Water is involved, directly or indirectly, with many activities and needs that have to be met. The large scale and importance of water projects, the investments needed, the difficulty in predicting the results, and the irreversible character of the decisions have made decision making a complex scientific process. This paper presents a multicriteria analysis (MCA) tool for evaluating water resource management (WRM) strategies and selecting the most appropriate among them, using as an example a Greek area based on agricultural economy, which faces water scarcity problems. Seven alternative strategies were evaluated under hydrological and economic criteria. Four techniques were used—multi attribute utility theory (MAUT), analytic hierarchy process (AHP), elimination and choice expressing reality (ELECTRE), and technique for order of preference by similarity to ideal solution (TOPSIS)—based on the main MCA techniques (utility theory, analytical hierarchy, outranking theory, and classification theory, respectively), to compare their performance, and to reach the most appropriate and ‘fitting’ method for the examined problem. The weightings extracted from two samples, (i) a sample of decision makers/stakeholders and (ii) a group of WRM experts, were used to compare the results. The process was carried out for each questionnaire, and thus the model shows the uncertainty of each sample group and of each method, as well as the overall uncertainty. The results illustrate the reality of the WRM problems of the watershed, enlighten their roots, and have further strengthened our conviction that the cooperation between the scientific community and the authorities is vital for more sustainable and efficient WRM.

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Tomic-Plazibat, Neli, Zdravka Aljinovic, and Snjezana Pivac. "Risk assessment of transitional economies by multivariate and multicriteria approaches." Panoeconomicus 57, no. 3 (2010): 283–302. http://dx.doi.org/10.2298/pan1003283t.

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This article assesses country-risk of sixteen Central, Baltic and South-East European transition countries, for 2005 and 2007, using multivariate cluster analysis. It was aided by the appropriate ANOVA (analysis of variance) testing and the multicriteria PROMETHEE method. The combination of methods makes for more accurate and efficient country-risk assessment. Country risk classifications and ratings involve evaluating the performance of countries while considering their economic and socio-political characteristics. The purpose of the article is to classify, and then find the comparative position of each individual country in the group of analyzed countries, in order to find out to which extent development of market economy and democratic society has been achieved.

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Radočaj, Dorijan, Mladen Jurišić, Mateo Gašparović, and Ivan Plaščak. "Optimal Soybean (Glycine max L.) Land Suitability Using GIS-Based Multicriteria Analysis and Sentinel-2 Multitemporal Images." Remote Sensing 12, no. 9 (May 5, 2020): 1463. http://dx.doi.org/10.3390/rs12091463.

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Soybean is regarded as one of the most produced crops in the world, presenting a source of high-quality protein for human and animal diets. The general objective of the study was to determine the optimal soybean land suitability and conduct its mapping based on the multicriteria analysis. The multicriteria analysis was based on Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) integration, using Sentinel-2 multitemporal images for suitability validation. The study area covered Osijek-Baranja County, a 4155 km2 area located in eastern Croatia. Three criteria standardization methods (fuzzy, stepwise and linear) were evaluated for soybean land suitability calculation. The delineation of soybean land suitability classes was performed by k-means unsupervised classification. An independent accuracy assessment of calculated suitability values was performed by a novel approach with peak Normalized Difference Vegetation Index (NDVI) values, derived from four Sentinel-2 multispectral satellite images. Fuzzy standardization with the combination of soil and climate criteria produced the most accurate suitability values, having the top coefficient of determination of 0.8438. A total of 14.5% of the study area (602 km2) was determined as the most suitable class for soybean cultivation based on k-means classification results, while 64.3% resulted in some degree of suitability.

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Spyridakos, Athanasios, Dimitrios E. Alexakis, Isaak Vryzidis, Nikolaos Tsotsolas, George Varelidis, and Efthimios Kagiaras. "Waste Classification of Spent Refractory Materials to Achieve Sustainable Development Goals Exploiting Multiple Criteria Decision Aiding Approach." Applied Sciences 12, no. 6 (March 16, 2022): 3016. http://dx.doi.org/10.3390/app12063016.

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The recycling of used refractory materials in the heavy industry constitutes one of the significant environmental problems in the industry related to environmental and financial issues. This study proposes a multicriteria methodological frame to characterize the refractory material waste and identify the recycling capabilities. Considering the chemical and physical analysis of the refractory material wastes, the proposed methodological frame progresses into a two-phase procedure. The first phase includes an on/off approach that allows discretizing the refractory material wastes to compatible or not compatible as far as their recycling prospects. Then, an additive value model is utilized, including (a) the marginal value functions used for every criterion related to critical environmental factors, and (b) the weight vector reflecting the relative importance of the criteria used. A group of experts concerning the environment and the refractory materials was employed to estimate the additive value model. The assessment of the marginal value function is achieved using the module of the Multicriteria Interactive Intelligence Decision Aiding System (MIIDAS), which is based on a modification of the mid-value split point technique incorporating focused dialogues, artificial intelligence, and visual techniques. The weight vector was assessed using the weight assessment through prioritization method (WAP), which concludes with the estimation of the weights based on the criteria ranking and the pairwise expression of the strength of preferences for the consecutive criteria according to their ranking. The outcome of this approach is to introduce an environmental appropriateness index for refractory materials based on their chemical composition and the judgement of an expert group. The main findings of this research may be useful for engineers, decision-makers, and scientists in the field of circular economy and waste management.

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Mukhametzyanov, Irik Z. "ReS-Algorithm for Converting Normalized Values of Cost Criteria Into Benefit Criteria in MCDM Tasks." International Journal of Information Technology & Decision Making 19, no. 05 (August 2020): 1389–423. http://dx.doi.org/10.1142/s0219622020500327.

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A review of modern methods of data normalization in the tasks of multicriteria decision-making and multidimensional classification is presented. The invariant properties of linear normalization methods are determined. Two basic principles of normalization of multidimensional data are defined: preservation of dispositions of natural and normalized values on the measurement scale and the absence of a displacement in the areas of normalized values of various criteria relative to each other. A method is proposed for converting normalized values of cost criteria to profit criteria based on the reverse sorting algorithm (ReS-algorithm). The ReS-algorithm preserves the dispositions of the natural and normalized values of the attributes of the alternatives and eliminates the displacement the areas of normalized values of the cost criteria relative to the profit criteria, which ensures the equality of the contributions of various criteria to the performance indicator of the alternatives.

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Pinheiro, Luana I. C. C., Maria Lúcia D. Pereira, Evandro C. de Andrade, Luciano C. Nunes, Wilson C. de Abreu, Pedro Gabriel Calíope D. Pinheiro, Raimir Holanda Filho, and Plácido Rogerio Pinheiro. "An Intelligent Multicriteria Model for Diagnosing Dementia in People Infected with Human Immunodeficiency Virus." Applied Sciences 11, no. 21 (November 7, 2021): 10457. http://dx.doi.org/10.3390/app112110457.

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Hybrid models to detect dementia based on Machine Learning can provide accurate diagnoses in individuals with neurological disorders and cognitive complications caused by Human Immunodeficiency Virus (HIV) infection. This study proposes a hybrid approach, using Machine Learning algorithms associated with the multicriteria method of Verbal Decision Analysis (VDA). Dementia, which affects many HIV-infected individuals, refers to neurodevelopmental and mental disorders. Some manuals standardize the information used in the correct detection of neurological disorders with cognitive complications. Among the most common manuals used are the DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition) of the American Psychiatric Association and the International Classification of Diseases, 10th edition (ICD-10)—both published by World Health Organization (WHO). The model is designed to explore the predictive of specific data. Furthermore, a well-defined database data set improves and optimizes the diagnostic models sought in the research.

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46

Kandasamy, Ilanthenral, and Florentin Smarandache. "Multicriteria Decision Making Using Double Refined Indeterminacy Neutrosophic Cross Entropy and Indeterminacy Based Cross Entropy." Applied Mechanics and Materials 859 (December 2016): 129–43. http://dx.doi.org/10.4028/www.scientific.net/amm.859.129.

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Double Refined Indeterminacy Neutrosophic Set (DRINS) is an inclusive case of the refined neutrosophic set, defined by Smarandache (2013), which provides the additional possibility to represent with sensitivity and accuracy the uncertain, imprecise, incomplete, and inconsistent information which are available in real world. More precision is provided in handling indeterminacy; by classifying indeterminacy (I) into two, based on membership; as indeterminacy leaning towards truth membership (IT) and indeterminacy leaning towards false membership (IF). This kind of classification of indeterminacy is not feasible with the existing Single Valued Neutrosophic Set (SVNS), but it is a particular case of the refined neutrosophic set (where each T, I, F can be refined into T1, T2, ...; I1, I2, ...; F1, F2, ...). DRINS is better equipped at dealing indeterminate and inconsistent information, with more accuracy than SVNS, which fuzzy sets and Intuitionistic Fuzzy Sets (IFS) are incapable of. Based on the cross entropy of neutrosophic sets, the cross entropy of DRINSs, known as Double Refined Indeterminacy neutrosophic cross entropy, is proposed in this paper. This proposed cross entropy is used for a multicriteria decision-making problem, where the criteria values for alternatives are considered under a DRINS environment. Similarly, an indeterminacy based cross entropy using DRINS is also proposed. The double valued neutrosophic weighted cross entropy and indeterminacy based cross entropy between the ideal alternative and an alternative is obtained and utilized to rank the alternatives corresponding to the cross entropy values. The most desirable one(s) in decision making process is selected. An illustrative example is provided to demonstrate the application of the proposed method. A brief comparison of the proposed method with the existing methods is carried out.

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Rodríguez Mañay, Luís Oswaldo, Inmaculada Guaita-Pradas, and Inmaculada Marques-Perez. "Measuring the Supply Chain Performance of the Floricultural Sector Using the SCOR Model and a Multicriteria Decision-Making Method." Horticulturae 8, no. 2 (February 16, 2022): 168. http://dx.doi.org/10.3390/horticulturae8020168.

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This study aims to highlight the usefulness of studying the performance of supply chains (SC) at the sectoral level in greater detail through the combination of a disaggregated supply chain operations reference (SCOR) model, with a multicriteria decision-making approach, specifically using an AHP, to adjust the analysis to the particularities of the sector under study by stakeholders’ judgements. The methodology was applied to the Ecuadorian flower industry, and the data for the analysis was from a survey of a group of companies that represent this sector. In addition, a focus group of SC experts weighted the model constructs as part of the analytic hierarchy process (AHP), and then the performance level for each construct was determined. According to the results methodologies, this model allows the classification of companies by their performance, as well as the performance of the aggregate sector. The processes that Ecuadorian flower companies need to improve on are planning, procurement, and manufacturing. The study’s main contribution is developing a general framework for measuring the overall performance of SCs and how the results are obtained. This tool could help managers, consultants, industries, and governments to assess the performance of SCs, as well as improving SC management in order to increase the sector’s competitiveness in the international market.

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Assis, Lucas Brandão Monteiro de, and Paulo César Lima Segantine. "Proposal of a Multicriteria Method to Implement New Primary Health Care Units - a Case Study in São Carlos - SP." Revista Brasileira de Cartografia 73, no. 4 (October 18, 2021): 1071–85. http://dx.doi.org/10.14393/rbcv73n4-61718.

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Primary Health Care (PHC) is understood as the user's first contact with the Brazilian health system. The planning of PHC units is usually done based on political decisions, which neglect technical aspects related to the theme. The general objective of this study is to present a multicriteria method to assist in planning the implantation of new PHC units, through technical and objective criteria. Then this method is put into practice in the city of São Carlos - SP. The study used as the main tool the Geographic Information System (GIS), and evaluated the quality of six criteria, which are: (1) service area; (2) spatial constraints; (3) risk of natural events; (4) public transportation supply; (5) population distribution; and (6) average income. Each criterion was based on a series of indicators with clear definitions that allowed for the assignment of values according to the theme of the criterion. Each criterion culminated in a thematic map, which, when combined through a raster calculator, allowed the general classification of the study area and the viability of implanting new PHC units. The proposed method proved to be a technical and objective tool, capable of helping in the planning of new PHC units. This is exemplified in the case study in the city of São Carlos- SP.

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Simão Filho, Marum, Plácido R. Pinheiro, Adriano B. Albuquerque, Régis P. S. Simão, Raimundo S. N. Azevedo, and Luciano C. Nunes. "A Multicriteria Approach to Support Task Allocation in Projects of Distributed Software Development." Complexity 2019 (April 1, 2019): 1–22. http://dx.doi.org/10.1155/2019/3926798.

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Organizations are increasingly investing in Distributed Software Development (DSD) over the years. A typical decision-making problem in the distributed scenario consists of deciding which team should be allocated each task. That decision takes into account a relative degree of subjectivity. That setting is suitable for applying Verbal Decision Analysis (VDA). This paper introduces an approach to support the allocation of tasks to distributed units in DSD projects, structured on the hybridisation of methods of Verbal Decision Analysis for classification and rank ordering applied to influencing factors and executing units. Firstly, a review of the literature was conducted aiming to identify the approaches to support the allocation of tasks in DSD contexts. Then, an approach was developed by applying VDA-based methods for classification and ordering. Bibliographic research and the application of surveys with professionals allowed identifying and characterising the main elements that influence task assignment in DSD projects. Afterwards, experiences were carried out in five real-world companies. In the end, the proposed approach has been submitted to the evaluation by the professionals of the participating companies and by some project management experts. The proposed approach comprises a workflow containing responsible actors and descriptions of the activities. Automated tools are also employed in automating the implementation of the approach. After applying the approach in five companies, task assignment recommendations are presented in groups for each company, according to the task type, i.e., requirements, architecture, coding, and testing, ranging from the most to the least preferable office. Results of the experiences and evaluations held during this work present evidence that the proposed approach is flexible, adaptable, and easy to understand and to use. Moreover, it helps to reduce decision subjectivity and to think of new aspects, supporting the task allocation process in DSD.

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Flores, X., A. Bonmatí, M. Poch, I. R. Roda, L. Jiménez, and R. Bañares-Alcántara. "Multicriteria evaluation tools to support the conceptual design of activated sludge systems." Water Science and Technology 56, no. 6 (September 1, 2007): 85–94. http://dx.doi.org/10.2166/wst.2007.587.

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During the past decade the pressure of the whole spectrum of stakeholders has increased considerably leading the consideration of different types of objectives, i.e. economical, technical, legal and environmental, into the process design efforts. Thus, the traditional design approaches should turn into more complex assessment methods including different types of objectives in order to conduct integrated assessments. The objective of this paper is to present and discuss the usefulness of three evaluation tools, based on multicriteria decision analysis, to support the conceptual design of activated sludge systems These support tools consist of: i) preliminary multiobjective optimization, where the most promising options (those located near to the optimum) are compared based on the results of dynamic simulation, ii) identification of strong and weak points for each option by means of classification trees and the subsequent extraction of knowledge-based rules, and iii) evaluation of the trade-offs between a certain evaluation criteria and the overall process performance through the integrated application of mathematical modelling and qualitative knowledge extracted during the design process.

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