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To improve the decision-making process, more and more systems are being developed based on a group of multi-criteria decision analysis (MCDA) methods. Each method is based on different approaches leading to a final result. It is possible to modify the default performance of these methods, but in this case, it is worth checking whether it affects the achieved results. In this paper, the technique for order preference by similarity to an ideal solution (TOPSIS) method was used to examine the chosen distance metric’s influence to obtained results. The Euclidean and Manhattan distances were compared, while obtained rankings were compared with the similarity coefficients to check their correlation. It shows that used distance metric has an impact on the results and they are significantly different.
Bartłomiej Kizielewicz; Jakub Więckowski; Jarosław Wątrobski. A Study of Different Distance Metrics in the TOPSIS Method. Intelligent Decision Technologies 2021, 275 -284.
AMA StyleBartłomiej Kizielewicz, Jakub Więckowski, Jarosław Wątrobski. A Study of Different Distance Metrics in the TOPSIS Method. Intelligent Decision Technologies. 2021; ():275-284.
Chicago/Turabian StyleBartłomiej Kizielewicz; Jakub Więckowski; Jarosław Wątrobski. 2021. "A Study of Different Distance Metrics in the TOPSIS Method." Intelligent Decision Technologies , no. : 275-284.
The decision-making process is a difficult problem, requiring the decision maker to consider the pros and cons of given options. Systems based on multi-criteria methods are increasingly used to support this. However, their number affects the difficulty of determining which of them is the right choice for a given problem and whether they guarantee similar results. In this paper, the three selected multi-critieria decision analysis (MCDA) methods were used to provide preferences values for alternatives. Decision matrix was created using different number of alternatives and criteria to check the impact of this change to final results. Three rankings were then subjected to two correlation coefficients. It shows that obtained rankings are highly similar, and greater amount of alternatives and criteria have a positive impact on received similarity.
Andrii Shekhovtsov; Jakub Więckowski; Jarosław Wątróbski. Toward Reliability in the MCDA Rankings: Comparison of Distance-Based Methods. Intelligent Decision Technologies 2021, 321 -329.
AMA StyleAndrii Shekhovtsov, Jakub Więckowski, Jarosław Wątróbski. Toward Reliability in the MCDA Rankings: Comparison of Distance-Based Methods. Intelligent Decision Technologies. 2021; ():321-329.
Chicago/Turabian StyleAndrii Shekhovtsov; Jakub Więckowski; Jarosław Wątróbski. 2021. "Toward Reliability in the MCDA Rankings: Comparison of Distance-Based Methods." Intelligent Decision Technologies , no. : 321-329.
The randomness of data appears in many problems in various fields. Stochastic optimization methods are often used to solve such problems. However, a large number of methods developed makes it difficult to determine which method is the optimal choice for solving a given problem. In this paper, the cat swarm optimization (CSO) was used to find the optimal preference values of characteristic objects, which were then subjected to applying the characteristic objects method (COMET). The determined problem was solved using the randomly chosen training and testing sets, where both were subjected to two criteria. The study’s motivation was to analyze the effectiveness of the CSO algorithm compared to other stochastic methods in solving problems of a similar class. The obtained solution shows that the used algorithm can be effectively applied to the defined problem, noting much better results than previously tested methods.
Jakub Więckowski; Andrii Shekhovtsov; Jarosław Wątróbski. A New Approach to Identifying of the Optimal Preference Values in the MCDA Model: Cat Swarm Optimization Study Case. Intelligent Decision Technologies 2021, 265 -274.
AMA StyleJakub Więckowski, Andrii Shekhovtsov, Jarosław Wątróbski. A New Approach to Identifying of the Optimal Preference Values in the MCDA Model: Cat Swarm Optimization Study Case. Intelligent Decision Technologies. 2021; ():265-274.
Chicago/Turabian StyleJakub Więckowski; Andrii Shekhovtsov; Jarosław Wątróbski. 2021. "A New Approach to Identifying of the Optimal Preference Values in the MCDA Model: Cat Swarm Optimization Study Case." Intelligent Decision Technologies , no. : 265-274.
Ambiguous and uncertain facts can be handled using a hesitant 2-tuple linguistic set (H2TLS), an important expansion of the 2-tuple linguistic set. The vagueness and uncertainty of data can be grabbed by using aggregation operators. Therefore, aggregation operators play an important role in computational processes to merge the information provided by decision makers (DMs). Furthermore, the aggregation operator is a potential mechanism for merging multisource data which is synonymous with cooperative preference. The aggregation operators need to be studied and analyzed from various perspectives to represent complex choice situations more readily and capture the diverse experiences of DMs. In this manuscript, we propose some valuable operational laws for H2TLS. These new operational laws work through the individual aggregation of linguistic words and the collection of translation parameters. We introduced a hesitant 2-tuple linguistic weighted average (H2TLWA) operator to solve multi-criteria group decision-making (MCGDM) problems. We also define hesitant 2-tuple linguistic Bonferroni mean (H2TLBM) operator, hesitant 2-tuple linguistic geometric Bonferroni mean (H2TLGBM) operator, hesitant 2-tuple linguistic Heronian mean (H2TLHM) operator, and a hesitant 2-tuple linguistic geometric Heronian mean (H2TLGHM) operator based on the novel operational laws proposed in this paper. We define the aggregation operators for addition, subtraction, multiplication, division, scalar multiplication, power and complement with their respective properties. An application example and comparison analysis were examined to show the usefulness and practicality of the work.
Shahzad Faizi; Wojciech Sałabun; Nisbha Shaheen; Atiq Rehman; Jarosław Wątróbski. A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment. Mathematics 2021, 9, 1489 .
AMA StyleShahzad Faizi, Wojciech Sałabun, Nisbha Shaheen, Atiq Rehman, Jarosław Wątróbski. A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment. Mathematics. 2021; 9 (13):1489.
Chicago/Turabian StyleShahzad Faizi; Wojciech Sałabun; Nisbha Shaheen; Atiq Rehman; Jarosław Wątróbski. 2021. "A Novel Multi-Criteria Group Decision-Making Approach Based on Bonferroni and Heronian Mean Operators under Hesitant 2-Tuple Linguistic Environment." Mathematics 9, no. 13: 1489.
Information spreading and influence maximization in social networks attracts attention from researchers from various disciplines. Majority of the existing studies focus on maximizing global coverage in the social network through initial seeds selection. In reality, networks are heterogeneous and different nodes can be a goal depending on campaign objectives. In this paper a novel approach with multi-attribute targeted influence maximization is proposed. The approach uses the multi-attribute nature of the network nodes (age, gender etc.) to better target specified groups of users. The proposed approach is verified on a real network and compared to the classic approaches delivers 7.14% coverage increase.
Artur Karczmarczyk; Jarosław Jankowski; Jarosław Wątrobski. Multi-criteria Seed Selection for Targeted Influence Maximization Within Social Networks. Transactions on Petri Nets and Other Models of Concurrency XV 2021, 454 -461.
AMA StyleArtur Karczmarczyk, Jarosław Jankowski, Jarosław Wątrobski. Multi-criteria Seed Selection for Targeted Influence Maximization Within Social Networks. Transactions on Petri Nets and Other Models of Concurrency XV. 2021; ():454-461.
Chicago/Turabian StyleArtur Karczmarczyk; Jarosław Jankowski; Jarosław Wątrobski. 2021. "Multi-criteria Seed Selection for Targeted Influence Maximization Within Social Networks." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 454-461.
Artificial Neural Networks (ANNs) have proven to be a powerful tool for solving a wide variety of real-life problems. The possibility of using them for forecasting phenomena occurring in nature, especially weather indicators, has been widely discussed. However, the various areas of the world differ in terms of their difficulty and ability in preparing accurate weather forecasts. Poland lies in a zone with a moderate transition climate, which is characterized by seasonality and the inflow of many types of air masses from different directions, which, combined with the compound terrain, causes climate variability and makes it difficult to accurately predict the weather. For this reason, it is necessary to adapt the model to the prediction of weather conditions and verify its effectiveness on real data. The principal aim of this study is to present the use of a regressive model based on a unidirectional multilayer neural network, also called a Multilayer Perceptron (MLP), to predict selected weather indicators for the city of Szczecin in Poland. The forecast of the model we implemented was effective in determining the daily parameters at 96% compliance with the actual measurements for the prediction of the minimum and maximum temperature for the next day and 83.27% for the prediction of atmospheric pressure.
Aleksandra Bączkiewicz; Jarosław Wątróbski; Wojciech Sałabun; Joanna Kołodziejczyk. An ANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions. Applied Sciences 2021, 11, 4757 .
AMA StyleAleksandra Bączkiewicz, Jarosław Wątróbski, Wojciech Sałabun, Joanna Kołodziejczyk. An ANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions. Applied Sciences. 2021; 11 (11):4757.
Chicago/Turabian StyleAleksandra Bączkiewicz; Jarosław Wątróbski; Wojciech Sałabun; Joanna Kołodziejczyk. 2021. "An ANN Model Trained on Regional Data in the Prediction of Particular Weather Conditions." Applied Sciences 11, no. 11: 4757.
This paper comprises the introduction of weighted mean products of fuzzy graph structures ( FGSs ) to construct weighted mean fuzzy graph structures ( WMFGSs ) with the help of optimization parameter, and establish some novel results after validating with examples, accordingly. The notions of regular and
Atiq Ur Rehman; Wojciech Salabun; Shahzad Faizi; Muhammad Hussain; Jaroslaw Watrobski. On Graph Structures in Fuzzy Environment Using Optimization Parameter. IEEE Access 2021, 9, 75699 -75711.
AMA StyleAtiq Ur Rehman, Wojciech Salabun, Shahzad Faizi, Muhammad Hussain, Jaroslaw Watrobski. On Graph Structures in Fuzzy Environment Using Optimization Parameter. IEEE Access. 2021; 9 ():75699-75711.
Chicago/Turabian StyleAtiq Ur Rehman; Wojciech Salabun; Shahzad Faizi; Muhammad Hussain; Jaroslaw Watrobski. 2021. "On Graph Structures in Fuzzy Environment Using Optimization Parameter." IEEE Access 9, no. : 75699-75711.
Sometimes in the sense of intuitionist 2-tuple linguistic (I2TL) sets, experts may not be able to decide the most suitable criterion weight vector for multicriteria decision making (MCDM). To avoid this situation, the decision-makers (DMs) can use the Best-Worst method (BWM), in which DMs choose the best (most significant) criterion and the worst (least significant) criterion and then provide two preference vectors by comparing criteria best to other (BO) and other to worst (OW). In the Nonlinear Best-Worst Method (NBWM) it is more complicated to find the unique solution of the model. Therefore, the main goal of this study is to propose two approaches to BWM, namely, Linear Best-Worst Method (LBWM) and Euclidean Best-Worst method (EBWM) to achieve the best criteria priority vector for Multi-Criteria Group Decision Making (MCGDM) problems in the context of I2TL information. In the computational process of MCDM problems, we have to aggregate I2TL elements into a global one. Consequently, under certain critical properties, we are creating some operational laws for I2TL elements based on Hamacher operations. Also, the intuitionistic 2-tuple linguistic Hamacher weighted average (I2TLHWA), and the intuitionistic 2-tuple linguistic Hamacher weighted geometric (I2TLHWG) operators are introduced with the assistance of Hamacher operations and I2TL elements. Subsequently, we analyze some of the I2TLHWA operator’s related properties and we propose MCGDM framework under I2TL information. Finally we demonstrate the validity and efficiency of our method and operations.
Shahzad Faizi; Wojciech Sałabun; Shoaib Nawaz; Atiq Ur Rehman; Jarosław W. atróbski. Best-Worst method and Hamacher aggregation operations for intuitionistic 2-tuple linguistic sets. Expert Systems with Applications 2021, 181, 115088 .
AMA StyleShahzad Faizi, Wojciech Sałabun, Shoaib Nawaz, Atiq Ur Rehman, Jarosław W. atróbski. Best-Worst method and Hamacher aggregation operations for intuitionistic 2-tuple linguistic sets. Expert Systems with Applications. 2021; 181 ():115088.
Chicago/Turabian StyleShahzad Faizi; Wojciech Sałabun; Shoaib Nawaz; Atiq Ur Rehman; Jarosław W. atróbski. 2021. "Best-Worst method and Hamacher aggregation operations for intuitionistic 2-tuple linguistic sets." Expert Systems with Applications 181, no. : 115088.
Online environments have evolved from the early-stage technical systems to social platforms with social communication mechanisms resembling the interactions which can be found in the real world. Online marketers are using the close relations between the users of social networks to more easily propagate the marketing contents in their advertising campaigns. Such viral marketing campaigns have proven to provide better results than traditional online marketing, hence the increasing research interest in the topic. While the majority of the up-to-date research focuses on maximizing the global coverage and influence in the complete network, some studies have been conducted in the area of budget-constrained conditions as well as in the area of targeting particular groups of nodes. In this paper, a novel approach to targeting multi-attribute nodes in complex networks is presented, in which an MCDA method with various preference weights for all criteria is used to select the initial seeds to best reach the targeted nodes in the network. The proposed approach shows some symmetric characteristics—while the global coverage in the network is decreased, the coverage amongst the targeted nodes grows.
Artur Karczmarczyk; Jarosław Jankowski; Jarosław Wątrobski. Multi-Criteria Seed Selection for Targeting Multi-Attribute Nodes in Complex Networks. Symmetry 2021, 13, 731 .
AMA StyleArtur Karczmarczyk, Jarosław Jankowski, Jarosław Wątrobski. Multi-Criteria Seed Selection for Targeting Multi-Attribute Nodes in Complex Networks. Symmetry. 2021; 13 (4):731.
Chicago/Turabian StyleArtur Karczmarczyk; Jarosław Jankowski; Jarosław Wątrobski. 2021. "Multi-Criteria Seed Selection for Targeting Multi-Attribute Nodes in Complex Networks." Symmetry 13, no. 4: 731.
Online systems with the highest global audiences take form of widely-used social platforms. Their immense traffic resulted in increased attention from researchers into various phenomena including information propagation in social networks. Although there exist some libraries, such as igraph and netdep, which allow representation of graphs in the R language, due to continual appearance of new models and information spreading approaches, the researchers are usually forced to write their own scripts to perform actual simulations and study their results. In this paper, the authors propose an object-oriented library and environment in R, for running simulation experiments focused on information spreading within complex networks. Object-oriented programming paradigms such as encapsulation, separation of concerns and modularity were used in the proposed software, to provide researchers with a scalable framework allowing quick and easy creation of experimental scenarios for studying information propagation in complex networks. It also supports new approaches, not available in other libraries, related to spreading seeds over the time in a form of sequential seeding, as well as coordinated execution, making it possible to compare algorithms in invariable experimental conditions.
Artur Karczmarczyk; Jarosław Jankowski; Jarosław Wątróbski. OONIS — Object-Oriented Network Infection Simulator. SoftwareX 2021, 14, 100675 .
AMA StyleArtur Karczmarczyk, Jarosław Jankowski, Jarosław Wątróbski. OONIS — Object-Oriented Network Infection Simulator. SoftwareX. 2021; 14 ():100675.
Chicago/Turabian StyleArtur Karczmarczyk; Jarosław Jankowski; Jarosław Wątróbski. 2021. "OONIS — Object-Oriented Network Infection Simulator." SoftwareX 14, no. : 100675.
The paper undertakes the problem of proper structuring of multi-criteria decision support models. To achieve that, a methodological framework is proposed. The authors’ framework is the basis for the relevance analysis of individual criteria in any considered decision model. The formal foundations of the authors’ approach provide a reference set of Multi-Criteria Decision Analysis (MCDA) methods (TOPSIS, VIKOR, COMET) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). In the empirical research, a practical MCDA-based wind farm location problem was studied. Reference rankings of the decision variants were obtained, followed by a set of rankings in which particular criteria were excluded. This was the basis for testing the similarity of the obtained solutions sets, as well as for recommendations in terms of both indicating the high significance and the possible elimination of individual criteria in the original model. When carrying out the analyzes, both the positions in the final rankings, as well as the corresponding values of utility functions of the decision variants were studied. As a result of the detailed analysis of the obtained results, recommendations were presented in the field of reference criteria set for the considered decision problem, thus demonstrating the practical usefulness of the authors’ proposed approach. It should be pointed out that the presented study of criteria relevance is an important factor for objectification of the multi-criteria decision support processes.
Bartłomiej Kizielewicz; Jarosław Wątróbski; Wojciech Sałabun. Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study. Energies 2020, 13, 6548 .
AMA StyleBartłomiej Kizielewicz, Jarosław Wątróbski, Wojciech Sałabun. Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study. Energies. 2020; 13 (24):6548.
Chicago/Turabian StyleBartłomiej Kizielewicz; Jarosław Wątróbski; Wojciech Sałabun. 2020. "Identification of Relevant Criteria Set in the MCDA Process—Wind Farm Location Case Study." Energies 13, no. 24: 6548.
Decision support systems often involve taking into account many factors that influence the choice of existing options. Besides, given the expert’s uncertainty on how to express the relationships between the collected data, it is not easy to define how to choose optimal solutions. Such problems also arise in sport, where coaches or players have many variants to choose from when conducting training or selecting the composition of players for competitions. In this paper, an objective fuzzy inference system based on fuzzy logic to evaluate players in team sports is proposed on the example of football. Based on the Characteristic Objects Method (COMET), a multi-criteria model has been developed to evaluate players on the positions of forwards based on their match statistics. The study has shown that this method can be used effectively in assessing players based on their performance. The COMET method was chosen because of its unique properties. It is one of the few methods that allow identifying the model without giving weightings of decision criteria. Symmetrical and asymmetrical fuzzy triangular numbers were used in model identification. Using the calculated derivatives in the point, it turned out that the criteria weights change in the problem state space. This prevents the use of other multi-criteria decision analysis (MCDA) methods. However, we compare the obtained model with the Technique of Order Preference Similarity (TOPSIS) method in order to better show the advantage of the proposed approach. The results from the objectified COMET model were compared with subjective rankings such as Golden Ball and player value.
Wojciech Sałabun; Andrii Shekhovtsov; Dragan Pamučar; Jarosław Wątróbski; Bartłomiej Kizielewicz; Jakub Więckowski; Darko Bozanić; Karol Urbaniak; Bartosz Nyczaj. A Fuzzy Inference System for Players Evaluation in Multi-Player Sports: The Football Study Case. Symmetry 2020, 12, 2029 .
AMA StyleWojciech Sałabun, Andrii Shekhovtsov, Dragan Pamučar, Jarosław Wątróbski, Bartłomiej Kizielewicz, Jakub Więckowski, Darko Bozanić, Karol Urbaniak, Bartosz Nyczaj. A Fuzzy Inference System for Players Evaluation in Multi-Player Sports: The Football Study Case. Symmetry. 2020; 12 (12):2029.
Chicago/Turabian StyleWojciech Sałabun; Andrii Shekhovtsov; Dragan Pamučar; Jarosław Wątróbski; Bartłomiej Kizielewicz; Jakub Więckowski; Darko Bozanić; Karol Urbaniak; Bartosz Nyczaj. 2020. "A Fuzzy Inference System for Players Evaluation in Multi-Player Sports: The Football Study Case." Symmetry 12, no. 12: 2029.
The proportional-integral-derivative (PID) algorithm automatically adjusts the control output based on the difference between a set point and a measured process variable. The classical approach is broadly used in the majority of control systems. However, in complex problems, this approach is not efficient, especially when the exact mathematical formula is difficult to specify. Besides, it was already proven that highly nonlinear situations are also significantly limiting the usage of the PID algorithm, in contrast to the fuzzy algorithms, which often work correctly under such conditions. In the case of multidimensional objects, where many independently operating PID algorithms are currently used, it is worth considering the use of one fuzzy algorithm with many-input single-output (MISO) or many-input many-output (MIMO) structure. In this work, a MISO type chip is investigated in the study case on simulation of crane relocating container with the external distribution. It is an example of control objects that due to badly conditioned dynamic features (strong non-linearities) require the operator’s intervention in manual or semi-automatic mode. The possibility of fuzzy algorithm synthesis is analyzed with two linguistic variable inputs (distance from −100 to 500 mm and angle from −45∘ to 45∘). The output signal is the speed which is modelled as a linguistic power variable (in the domain from −100% to 100%). Based on 36 fuzzy rules, we present the main contribution, the control system with external disturbance, to show the effectiveness of the identified fuzzy PID approach with different gain values. The fuzzy control system and PID control are implemented and compared concerning the time taken for the container to reach the set point. The results show that fuzzy MISO PID is more effective than the classical one because fuzzy set theory helps to deal with the environmental uncertainty. The container’s angle deviations are taken into consideration, as mitigating them and simultaneously maintaining the fastest speed possible is an essential factor of this challenge.
Wojciech Sałabun; Jakub Więckowski; Andrii Shekhovtsov; Krzysztof Palczewski; Sławomir Jaszczak; Jarosław Wątróbski. How to Apply Fuzzy MISO PID in the Industry? An Empirical Study Case on Simulation of Crane Relocating Containers. Electronics 2020, 9, 2017 .
AMA StyleWojciech Sałabun, Jakub Więckowski, Andrii Shekhovtsov, Krzysztof Palczewski, Sławomir Jaszczak, Jarosław Wątróbski. How to Apply Fuzzy MISO PID in the Industry? An Empirical Study Case on Simulation of Crane Relocating Containers. Electronics. 2020; 9 (12):2017.
Chicago/Turabian StyleWojciech Sałabun; Jakub Więckowski; Andrii Shekhovtsov; Krzysztof Palczewski; Sławomir Jaszczak; Jarosław Wątróbski. 2020. "How to Apply Fuzzy MISO PID in the Industry? An Empirical Study Case on Simulation of Crane Relocating Containers." Electronics 9, no. 12: 2017.
This paper presents an improved consensus-based procedure to handle multi-person decision making (MPDM) using hesitant fuzzy preference relations (HFPRs) which are not in normal format. At the first level, we proposed a ukasiewicz transitivity (TL-transitivity) based scheme to get normalized hesitant fuzzy preference relations (NHFPRs), subject to which, a consensus-based model is established. Then, a transitive closure formula is defined to construct TL-consistent HFPRs and creates symmetrical matrices. Following this, consistency analysis is made to estimate the consistency degrees of the information provided by the decision-makers (DMs), and consequently, to assign the consistency weights to them. The final priority weights vector of DMs is calculated after the combination of consistency weights and predefined priority weights (if any). The consensus process concludes whether the aggregation of data and selection of the best alternative should be originated or not. The enhancement mechanism is indulged in improving the consensus measure among the DMs, after introducing an identifier used to locate the weak positions, in case of the poor consensus reached. In the end, a comparative example reflects the applicability and the efficiency of proposed scheme. The results show that the proposed method can offer useful comprehension into the MPDM process.
Atiq-Ur Rehman; Jarosław Wątróbski; Shahzad Faizi; Tabasam Rashid; Małgorzata Tarczyńska-Łuniewska. Sustainable Decision Making Using a Consensus Model for Consistent Hesitant Fuzzy Preference Relations—Water Allocation Management Case Study. Symmetry 2020, 12, 1957 .
AMA StyleAtiq-Ur Rehman, Jarosław Wątróbski, Shahzad Faizi, Tabasam Rashid, Małgorzata Tarczyńska-Łuniewska. Sustainable Decision Making Using a Consensus Model for Consistent Hesitant Fuzzy Preference Relations—Water Allocation Management Case Study. Symmetry. 2020; 12 (12):1957.
Chicago/Turabian StyleAtiq-Ur Rehman; Jarosław Wątróbski; Shahzad Faizi; Tabasam Rashid; Małgorzata Tarczyńska-Łuniewska. 2020. "Sustainable Decision Making Using a Consensus Model for Consistent Hesitant Fuzzy Preference Relations—Water Allocation Management Case Study." Symmetry 12, no. 12: 1957.
Human activity is moving steadily to virtual reality. More and more, people from all over the world are keen on growing fascination with e-sport. In practice, e-sport is a type of sport in which players compete using computer games. The competitions in games, like FIFA, Dota2, the League of Legends, and Counter-Strike, are prestigious tournaments with a global reach and a budget of millions of dollars. On the other hand, reliable player ranking is a critical issue in both classic and e-sport. For example, the “Golden Ball” is the most valuable prize for an individual football player in the whole football history. Moreover, the entire players’ world wants to know who the best player is. The position of each player in the ranking depends on the assessment of his skills and predispositions. In this paper, we studied identification of players evaluation and ranking obtained using the multiple-criteria decision-making based method called Characteristic Objects METhod (COMET) on the example of the popular game Counter-Strike: Global Offensive (CS: GO). We present a range of advantages of the player evaluation model created using the COMET method and, therefore, prove the practicality of using multi-criteria decision analysis (MCDA) methods to build multi-criteria assessment models in emerging areas of eSports. Thus, we provide a methodical and practical background for building a decision support system engine for the evaluation of players in several eSports.
Karol Urbaniak; Jarosław Wątróbski; Wojciech Sałabun. Identification of Players Ranking in E-Sport. Applied Sciences 2020, 10, 6768 .
AMA StyleKarol Urbaniak, Jarosław Wątróbski, Wojciech Sałabun. Identification of Players Ranking in E-Sport. Applied Sciences. 2020; 10 (19):6768.
Chicago/Turabian StyleKarol Urbaniak; Jarosław Wątróbski; Wojciech Sałabun. 2020. "Identification of Players Ranking in E-Sport." Applied Sciences 10, no. 19: 6768.
Multi-Criteria Decision-Analysis (MCDA) methods are successfully applied in different fields and disciplines. However, in many studies, the problem of selecting the proper methods and parameters for the decision problems is raised. The paper undertakes an attempt to benchmark selected Multi-Criteria Decision Analysis (MCDA) methods. To achieve that, a set of feasible MCDA methods was identified. Based on reference literature guidelines, a simulation experiment was planned. The formal foundations of the authors’ approach provide a reference set of MCDA methods ( Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), Complex Proportional Assessment (COPRAS), and PROMETHEE II: Preference Ranking Organization Method for Enrichment of Evaluations) along with their similarity coefficients (Spearman correlation coefficients and WS coefficient). This allowed the generation of a set of models differentiated by the number of attributes and decision variants, as well as similarity research for the obtained rankings sets. As the authors aim to build a complex benchmarking model, additional dimensions were taken into account during the simulation experiments. The aspects of the performed analysis and benchmarking methods include various weighing methods (results obtained using entropy and standard deviation methods) and varied techniques of normalization of MCDA model input data. Comparative analyses showed the detailed influence of values of particular parameters on the final form and a similarity of the final rankings obtained by different MCDA methods.
Wojciech Sałabun; Jarosław Wątróbski; Andrii Shekhovtsov. Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods. Symmetry 2020, 12, 1549 .
AMA StyleWojciech Sałabun, Jarosław Wątróbski, Andrii Shekhovtsov. Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods. Symmetry. 2020; 12 (9):1549.
Chicago/Turabian StyleWojciech Sałabun; Jarosław Wątróbski; Andrii Shekhovtsov. 2020. "Are MCDA Methods Benchmarkable? A Comparative Study of TOPSIS, VIKOR, COPRAS, and PROMETHEE II Methods." Symmetry 12, no. 9: 1549.
Over the past few decades, several researchers and professionals have focused on the development and application of multi-criteria group decision making (MCGDM) methods under a fuzzy environment in different areas and disciplines. This complex research area has become one of the more popular topics, and it seems that this trend will be increasing. In this paper, we propose a new MCGDM approach combining intuitionistic fuzzy sets (IFSs) and the Characteristic Object Method (COMET) for solving the group decision making (GDM) problems. The COMET method is resistant to the rank reversal phenomenon, and at the same time it remains relatively simple and intuitive in practical problems. This method can be used for both symmetric and asymmetric information. The Triangular Intuitionistic Fuzzy Numbers (TIFNs) have been used to handle uncertain data. This concept can ensure the preference information about an alternative under specific criteria more comprehensively and allows for easy modelling of symmetrical or asymmetrical linguistic values. Each expert provides the membership and non-membership degree values of intuitionistic fuzzy numbers (IFNs). So this approach deals with a different kind of uncertainty than with hesitant fuzzy sets (HFSs). The proposed combination of COMET and IFSs required an adaptation of the matrix of expert judgment (MEJ) and allowed to capture the behaviour aspects of the decision makers (DMs). Therefore, we get more reliable solutions while solving MCGDM problems. Finally, the proposed method is presented in a simple academic example.
Shahzad Faizi; Wojciech Sałabun; Tabasam Rashid; Sohail Zafar; Jarosław Wątróbski. Intuitionistic Fuzzy Sets in Multi-Criteria Group Decision Making Problems Using the Characteristic Objects Method. Symmetry 2020, 12, 1382 .
AMA StyleShahzad Faizi, Wojciech Sałabun, Tabasam Rashid, Sohail Zafar, Jarosław Wątróbski. Intuitionistic Fuzzy Sets in Multi-Criteria Group Decision Making Problems Using the Characteristic Objects Method. Symmetry. 2020; 12 (9):1382.
Chicago/Turabian StyleShahzad Faizi; Wojciech Sałabun; Tabasam Rashid; Sohail Zafar; Jarosław Wątróbski. 2020. "Intuitionistic Fuzzy Sets in Multi-Criteria Group Decision Making Problems Using the Characteristic Objects Method." Symmetry 12, no. 9: 1382.
A q-rung orthopair fuzzy set (q-ROFS), an extension of the Pythagorean fuzzy set (PFS) and intuitionistic fuzzy set (IFS), is very helpful in representing vague information that occurs in real-world circumstances. The intention of this article is to introduce several aggregation operators in the framework of q-rung orthopair fuzzy numbers (q-ROFNs). The key feature of q-ROFNs is to deal with the situation when the sum of the qth powers of membership and non-membership grades of each alternative in the universe is less than one. The Einstein operators with their operational laws have excellent flexibility. Due to the flexible nature of these Einstein operational laws, we introduce the q-rung orthopair fuzzy Einstein weighted averaging (q-ROFEWA) operator, q-rung orthopair fuzzy Einstein ordered weighted averaging (q-ROFEOWA) operator, q-rung orthopair fuzzy Einstein weighted geometric (q-ROFEWG) operator, and q-rung orthopair fuzzy Einstein ordered weighted geometric (q-ROFEOWG) operator. We discuss certain properties of these operators, inclusive of their ability that the aggregated value of a set of q-ROFNs is a unique q-ROFN. By utilizing the proposed Einstein operators, this article describes a robust multi-criteria decision making (MCDM) technique for solving real-world problems. Finally, a numerical example related to integrated energy modeling and sustainable energy planning is presented to justify the validity and feasibility of the proposed technique.
Muhammad Riaz; Wojciech Sałabun; Hafiz Muhammad Athar Farid; Nawazish Ali; Jarosław Wątróbski. A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management. Energies 2020, 13, 2155 .
AMA StyleMuhammad Riaz, Wojciech Sałabun, Hafiz Muhammad Athar Farid, Nawazish Ali, Jarosław Wątróbski. A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management. Energies. 2020; 13 (9):2155.
Chicago/Turabian StyleMuhammad Riaz; Wojciech Sałabun; Hafiz Muhammad Athar Farid; Nawazish Ali; Jarosław Wątróbski. 2020. "A Robust q-Rung Orthopair Fuzzy Information Aggregation Using Einstein Operations with Application to Sustainable Energy Planning Decision Management." Energies 13, no. 9: 2155.
Information spreading within social networks and techniques related to viral marketing has begun to attract more interest of online marketers. While much of the prior research focuses on increasing the coverage of the viral marketing campaign, in real-life applications also other campaign goals and limitations need to be considered, such as limited time or budget, or assumed dynamics of the process. This paper presents a multi-criteria approach to planning of information spreading processes, with focus on the campaign initialization with the use of sequential seeding. A framework and example set of criteria was proposed for evaluation of viral marketing campaign strategies. The initial results showed that an increase of the count of seeding iterations and the interval between them increases the achieved coverage at the cost of increased process duration, yet without the need to increase seeding fraction or to provide incentives for increased propagation probability.
Artur Karczmarczyk; Jarosław Wątróbski; Jarosław Jankowski. Multi-criteria Approach to Planning of Information Spreading Processes Focused on Their Initialization with the Use of Sequential Seeding. Business Information Systems 2020, 116 -134.
AMA StyleArtur Karczmarczyk, Jarosław Wątróbski, Jarosław Jankowski. Multi-criteria Approach to Planning of Information Spreading Processes Focused on Their Initialization with the Use of Sequential Seeding. Business Information Systems. 2020; ():116-134.
Chicago/Turabian StyleArtur Karczmarczyk; Jarosław Wątróbski; Jarosław Jankowski. 2020. "Multi-criteria Approach to Planning of Information Spreading Processes Focused on Their Initialization with the Use of Sequential Seeding." Business Information Systems , no. : 116-134.
The methods of multi-criteria decision analysis are widely used for problems of selecting the best solution or ordering their sets. In the vast majority of cases, solving multi-criteria decision-making problems focuses on finding solutions for a given set of alternatives. When, for one or more decisional variants, the values of their attributes change, or a new alternative for assessment appears, the problem occurs. Therefore, in this paper, we focus on identifying the full decision-making model in the issue related to the study case of production line optimization. In this work, the Characteristic Objects METhod (COMET) has been applied. In effect, it identifies the full decision-making model. The decision problem has been identified, taking into account six decision criteria, and its operation has been used in organizing four decision alternatives.
Szymon Rymaszewski; Jarosław Wątróbski; Artur Karczmarczyk. Identification of reference multi criteria domain model - Production line optimization case study. Procedia Computer Science 2020, 176, 3794 -3801.
AMA StyleSzymon Rymaszewski, Jarosław Wątróbski, Artur Karczmarczyk. Identification of reference multi criteria domain model - Production line optimization case study. Procedia Computer Science. 2020; 176 ():3794-3801.
Chicago/Turabian StyleSzymon Rymaszewski; Jarosław Wątróbski; Artur Karczmarczyk. 2020. "Identification of reference multi criteria domain model - Production line optimization case study." Procedia Computer Science 176, no. : 3794-3801.