PurposeNormalization is a crucial step in all decision models, to produce comparable and dimensio... more PurposeNormalization is a crucial step in all decision models, to produce comparable and dimensionless data from heterogeneous data. As such, various normalization techniques are available but their performance depends on a number of characteristics of the problem at hand. Thus, this study aims to introduce a recommendation framework for supporting users to select data normalization techniques that better fit the requirements in different application scenarios, based on multi-criteria decision methods.Design/methodology/approachFollowing the proposed approach, the authors compare six well-known normalization techniques applied to a case study of selecting suppliers in collaborative networks.FindingsWith this recommendation framework, the authors expect to contribute to improving the normalization of criteria in the evaluation and selection of suppliers and business partners in dynamic networked collaborative systems.Originality/valueThis is the first study about comparing normalization techniques for selecting the best normalization in dynamic multiple-criteria decision-making models in collaborative networks.
IFIP Advances in Information and Communication Technology
In recent years, data normalization is receiving considerable attention due to its essential role... more In recent years, data normalization is receiving considerable attention due to its essential role in decision problems. Especially, considering the new developments in Big data and Artificial Intelligent to handle heterogeneous data from sensors, normalization's role as a preprocessing step for complex decision problems is more distinguished. However, selecting the best normalization technique among several introduced techniques in the literature is still an open issue. In this study we focus on evaluating normalization techniques in Multi-Criteria Decision Making (MCDM) methods namely for Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to recommend the most proper technique. A small numerical example, borrowed from literature, is used to show the applicability of the proposed assessment framework using several metrics for recommending the most suitable technique. This study helps decision makers to improve the accuracy of the final ranking of results in decision problems by selecting the best normalization technique for the related case study.
One of the current topics of attention in data analysis is the selection of the best normalizatio... more One of the current topics of attention in data analysis is the selection of the best normalization technique in the aggregation process when using Multi-Criteria Decision Making (MCDM) methods for solving decision problems. This is particularly critical in complex collaborative decision-making systems dealing with a large variety of heterogeneous data sources. Using different normalization techniques may result in different rankings of alternatives. So, enhancing the accuracy of the final ranking of alternatives could be achieved by selecting the most proper normalization techniques for each MCDM decision problem. In this direction, several attempts have been carried out, however, the lack of coherence and lack of a robust assessment framework persist. This situation encouraged the authors to propose an assessment framework that is enriched with several metrics for the evaluation of different normalization techniques in MCDM problems with the focus on partner/supplier selection in collaborative networks. As an illustration of the approach, in this work we assess different normalization techniques with the Simple Additive Weighting (SAW) method using metrics from the proposed assessment framework and select the most adequate technique for a small case study that is borrowed from literature. The suggested approach contributes to increasing the accuracy of final results for MCDM methods.
Currently data heavily, constantly, and globally flows into all areas of our economy. Individuals... more Currently data heavily, constantly, and globally flows into all areas of our economy. Individuals and mainly organizations have to tackle the problem of processing large data in support of their respective needs and operations, aiming at improving their manageability and efficiency. Big Data urges for advances in technology and cannot count anymore with classical database tools to manage and analyze information data-sets. This work positions the importance of Decision Making and DSS to exploit Big Data analysis so that organizations can get ready to compete with high productivity.
Advances in Intelligent Systems and Computing, 2020
Nowadays, interoperable decision support systems play a crucial role to improve production activi... more Nowadays, interoperable decision support systems play a crucial role to improve production activity control in industrial Companies, and enable them to face the growing exigencies imposed by the arising Industry 4.0 era. In this paper an interoperable decision support system based on multivariate time series for setup data processing and visualization is put forward. The proposed system is described, in the context of a general architecture presented, and its application through an illustrative example from a stamping factory is analysed. Through the case study it is possible to realize about the importance of the proposed system, and its suitability of application to other companies, for instance in other industrial sectors and manufacturing environments.
IFIP Advances in Information and Communication Technology, 2018
One of the main challenges when evaluating resilience frameworks is the aggregation of different ... more One of the main challenges when evaluating resilience frameworks is the aggregation of different criteria. To calculate the final level of resilience we have to measure different criteria and then fuse the information to obtain a score. Normalization is a crucial step in any decision making process of evaluation of alternatives or frameworks. Normalization transforms heterogeneous criteria data (qualitative, quantitative, different units, etc.) into numerical and comparable data to enable aggregation (fusion) of criteria to determine the rating of decision alternatives. In this study, we evaluate the effects of different normalization techniques on the most well-known multi-criteria (MCDM) method, called Weighted Average (WA) or SAW (Simple Additive Weighting). A small case study for selecting resilience frameworks illustrates our assessment process for selecting the suitable normalization technique.
The great abundance of multi-sensor traffic data (traditional traffic data sources loops, cameras... more The great abundance of multi-sensor traffic data (traditional traffic data sources loops, cameras and radars accompanied or even replaced by the most recent Bluetooth detectors, GPS enabled floating car data) although offering the chance to exploit Big Data advantages in traffic planning, management and monitoring, has also opened the debate on data cleaning, fusion and interpretation techniques. The current paper concentrates on floating taxi data in the case of a Greek city, Thessaloniki city, and proposes the use of advanced spatiotemporal dynamics identification techniques among urban road paths for gaining a deep understanding of complex relations among them. The visualizations deriving from the advanced time series analysis proposed (hereinafter referred also as knowledge graphs) facilitate the understanding of the relations and the potential future reactions/outcomes of urban traffic management and calming interventions, enhances communication potentials (useful and consumabl...
International Journal of Decision Support System Technology, 2022
With the fast growing of data-rich systems, dealing with complex decision problems with skewed in... more With the fast growing of data-rich systems, dealing with complex decision problems with skewed input data sets and respective outliers is unavoidable. Generally, data skewness refers to a non-uniform distribution in a dataset, i.e. a dataset which contains asymmetries and/or outliers. Normalization is the first step of most multi-criteria decision making (MCDM) problems to obtain dimensionless data, from heterogeneous input data sets, that enable aggregation of criteria and thereby ranking of alternatives. Therefore, when in presence of outliers in criteria datasets, finding a suitable normalization technique is of utmost importance. As such, in this work, we compare seven normalization techniques (Max, Max-Min, Vector, Sum, Logarithmic, Target-based, and Fuzzification) on criteria datasets, which contain outliers to analyse their results for MCDM problems. A numerical example illustrates the behaviour of the chosen normalization techniques and an (ongoing) evaluation assessment fra...
The difficult job of fighting fires and the nearly impossible task to stop a wildfire without gre... more The difficult job of fighting fires and the nearly impossible task to stop a wildfire without great casualties requires an imperative implementation of proactive strategies. These strategies must decrease the number of fires, the burnt area and create better conditions for the firefighting. In this line of action, the Portuguese Institute of Nature and Forest Conservation defined a fire break network (FBN), which helps controlling wildfires. However, these fire breaks are efficient only if they are correctly maintained, which should be ensured by the local authorities and requires verification from the national authorities. This is a fastidious task since they have a large network of thousands of hectares to monitor over a full year. With the increasing quality and frequency of the Earth Observation Satellite imagery with Sentinel-2 and the definition of the FBN, a semi-automatic remote sensing methodology is proposed in this article for the detection of maintenance operations in a ...
In Dargam F Delibasic B Hern Ndez J E Liu S Ribeiro R Zarat P Decision Support Systems Operations Management Trends and Solutions in Industries Euro Working Group For Decision Support System 12 Apr 2012 13 Apr 2012 Liverpool Uk Ewgss Wordpress 2012, Apr 12, 2012
International Journal of Decision Support System Technology, 2016
Driving a car is a complex skill that includes interacting with multiple systems inside the vehic... more Driving a car is a complex skill that includes interacting with multiple systems inside the vehicle. Today's challenge in the automotive industry is to produce innovative In-Vehicle Information Systems (IVIS) that are pleasant to use and satisfy the costumers' needs while, simultaneously, maintaining the delicate balance of primary task vs. secondary tasks while driving. The authors report a MCDM approach for rank ordering a large heterogeneous set of human-machine interaction technologies; the final set consisted of hundred and one candidates. They measured candidate technologies on eight qualitative criteria that were defined by domain experts, using a group decision-making approach. The main objective was ordering alternatives by their decision score, not the selection of one or a small set of them. The authors' approach assisted decision makers in exploring the characteristics of the most promising technologies and they focused on analyzing the technologies in the to...
PurposeNormalization is a crucial step in all decision models, to produce comparable and dimensio... more PurposeNormalization is a crucial step in all decision models, to produce comparable and dimensionless data from heterogeneous data. As such, various normalization techniques are available but their performance depends on a number of characteristics of the problem at hand. Thus, this study aims to introduce a recommendation framework for supporting users to select data normalization techniques that better fit the requirements in different application scenarios, based on multi-criteria decision methods.Design/methodology/approachFollowing the proposed approach, the authors compare six well-known normalization techniques applied to a case study of selecting suppliers in collaborative networks.FindingsWith this recommendation framework, the authors expect to contribute to improving the normalization of criteria in the evaluation and selection of suppliers and business partners in dynamic networked collaborative systems.Originality/valueThis is the first study about comparing normalization techniques for selecting the best normalization in dynamic multiple-criteria decision-making models in collaborative networks.
IFIP Advances in Information and Communication Technology
In recent years, data normalization is receiving considerable attention due to its essential role... more In recent years, data normalization is receiving considerable attention due to its essential role in decision problems. Especially, considering the new developments in Big data and Artificial Intelligent to handle heterogeneous data from sensors, normalization's role as a preprocessing step for complex decision problems is more distinguished. However, selecting the best normalization technique among several introduced techniques in the literature is still an open issue. In this study we focus on evaluating normalization techniques in Multi-Criteria Decision Making (MCDM) methods namely for Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to recommend the most proper technique. A small numerical example, borrowed from literature, is used to show the applicability of the proposed assessment framework using several metrics for recommending the most suitable technique. This study helps decision makers to improve the accuracy of the final ranking of results in decision problems by selecting the best normalization technique for the related case study.
One of the current topics of attention in data analysis is the selection of the best normalizatio... more One of the current topics of attention in data analysis is the selection of the best normalization technique in the aggregation process when using Multi-Criteria Decision Making (MCDM) methods for solving decision problems. This is particularly critical in complex collaborative decision-making systems dealing with a large variety of heterogeneous data sources. Using different normalization techniques may result in different rankings of alternatives. So, enhancing the accuracy of the final ranking of alternatives could be achieved by selecting the most proper normalization techniques for each MCDM decision problem. In this direction, several attempts have been carried out, however, the lack of coherence and lack of a robust assessment framework persist. This situation encouraged the authors to propose an assessment framework that is enriched with several metrics for the evaluation of different normalization techniques in MCDM problems with the focus on partner/supplier selection in collaborative networks. As an illustration of the approach, in this work we assess different normalization techniques with the Simple Additive Weighting (SAW) method using metrics from the proposed assessment framework and select the most adequate technique for a small case study that is borrowed from literature. The suggested approach contributes to increasing the accuracy of final results for MCDM methods.
Currently data heavily, constantly, and globally flows into all areas of our economy. Individuals... more Currently data heavily, constantly, and globally flows into all areas of our economy. Individuals and mainly organizations have to tackle the problem of processing large data in support of their respective needs and operations, aiming at improving their manageability and efficiency. Big Data urges for advances in technology and cannot count anymore with classical database tools to manage and analyze information data-sets. This work positions the importance of Decision Making and DSS to exploit Big Data analysis so that organizations can get ready to compete with high productivity.
Advances in Intelligent Systems and Computing, 2020
Nowadays, interoperable decision support systems play a crucial role to improve production activi... more Nowadays, interoperable decision support systems play a crucial role to improve production activity control in industrial Companies, and enable them to face the growing exigencies imposed by the arising Industry 4.0 era. In this paper an interoperable decision support system based on multivariate time series for setup data processing and visualization is put forward. The proposed system is described, in the context of a general architecture presented, and its application through an illustrative example from a stamping factory is analysed. Through the case study it is possible to realize about the importance of the proposed system, and its suitability of application to other companies, for instance in other industrial sectors and manufacturing environments.
IFIP Advances in Information and Communication Technology, 2018
One of the main challenges when evaluating resilience frameworks is the aggregation of different ... more One of the main challenges when evaluating resilience frameworks is the aggregation of different criteria. To calculate the final level of resilience we have to measure different criteria and then fuse the information to obtain a score. Normalization is a crucial step in any decision making process of evaluation of alternatives or frameworks. Normalization transforms heterogeneous criteria data (qualitative, quantitative, different units, etc.) into numerical and comparable data to enable aggregation (fusion) of criteria to determine the rating of decision alternatives. In this study, we evaluate the effects of different normalization techniques on the most well-known multi-criteria (MCDM) method, called Weighted Average (WA) or SAW (Simple Additive Weighting). A small case study for selecting resilience frameworks illustrates our assessment process for selecting the suitable normalization technique.
The great abundance of multi-sensor traffic data (traditional traffic data sources loops, cameras... more The great abundance of multi-sensor traffic data (traditional traffic data sources loops, cameras and radars accompanied or even replaced by the most recent Bluetooth detectors, GPS enabled floating car data) although offering the chance to exploit Big Data advantages in traffic planning, management and monitoring, has also opened the debate on data cleaning, fusion and interpretation techniques. The current paper concentrates on floating taxi data in the case of a Greek city, Thessaloniki city, and proposes the use of advanced spatiotemporal dynamics identification techniques among urban road paths for gaining a deep understanding of complex relations among them. The visualizations deriving from the advanced time series analysis proposed (hereinafter referred also as knowledge graphs) facilitate the understanding of the relations and the potential future reactions/outcomes of urban traffic management and calming interventions, enhances communication potentials (useful and consumabl...
International Journal of Decision Support System Technology, 2022
With the fast growing of data-rich systems, dealing with complex decision problems with skewed in... more With the fast growing of data-rich systems, dealing with complex decision problems with skewed input data sets and respective outliers is unavoidable. Generally, data skewness refers to a non-uniform distribution in a dataset, i.e. a dataset which contains asymmetries and/or outliers. Normalization is the first step of most multi-criteria decision making (MCDM) problems to obtain dimensionless data, from heterogeneous input data sets, that enable aggregation of criteria and thereby ranking of alternatives. Therefore, when in presence of outliers in criteria datasets, finding a suitable normalization technique is of utmost importance. As such, in this work, we compare seven normalization techniques (Max, Max-Min, Vector, Sum, Logarithmic, Target-based, and Fuzzification) on criteria datasets, which contain outliers to analyse their results for MCDM problems. A numerical example illustrates the behaviour of the chosen normalization techniques and an (ongoing) evaluation assessment fra...
The difficult job of fighting fires and the nearly impossible task to stop a wildfire without gre... more The difficult job of fighting fires and the nearly impossible task to stop a wildfire without great casualties requires an imperative implementation of proactive strategies. These strategies must decrease the number of fires, the burnt area and create better conditions for the firefighting. In this line of action, the Portuguese Institute of Nature and Forest Conservation defined a fire break network (FBN), which helps controlling wildfires. However, these fire breaks are efficient only if they are correctly maintained, which should be ensured by the local authorities and requires verification from the national authorities. This is a fastidious task since they have a large network of thousands of hectares to monitor over a full year. With the increasing quality and frequency of the Earth Observation Satellite imagery with Sentinel-2 and the definition of the FBN, a semi-automatic remote sensing methodology is proposed in this article for the detection of maintenance operations in a ...
In Dargam F Delibasic B Hern Ndez J E Liu S Ribeiro R Zarat P Decision Support Systems Operations Management Trends and Solutions in Industries Euro Working Group For Decision Support System 12 Apr 2012 13 Apr 2012 Liverpool Uk Ewgss Wordpress 2012, Apr 12, 2012
International Journal of Decision Support System Technology, 2016
Driving a car is a complex skill that includes interacting with multiple systems inside the vehic... more Driving a car is a complex skill that includes interacting with multiple systems inside the vehicle. Today's challenge in the automotive industry is to produce innovative In-Vehicle Information Systems (IVIS) that are pleasant to use and satisfy the costumers' needs while, simultaneously, maintaining the delicate balance of primary task vs. secondary tasks while driving. The authors report a MCDM approach for rank ordering a large heterogeneous set of human-machine interaction technologies; the final set consisted of hundred and one candidates. They measured candidate technologies on eight qualitative criteria that were defined by domain experts, using a group decision-making approach. The main objective was ordering alternatives by their decision score, not the selection of one or a small set of them. The authors' approach assisted decision makers in exploring the characteristics of the most promising technologies and they focused on analyzing the technologies in the to...
Normalization in multi criteria decision making methods (MCDM) is the process of transforming het... more Normalization in multi criteria decision making methods (MCDM) is the process of transforming heterogeneous input data (qualitative, quantitative, different unit s, etc.) into numerical and comparable data to enable aggregation (fusion) of criteria to determine the rating of decision alternatives. Therefore, normalization is a crucial step for any MCDM method. In this paper we have a preliminary discussion about an assessment process for finding suitable normalization techniques for three well known MCDM methods: ELECTRE (ELimination and Choice Expressing REality); SAW (Simple Additive Weighting); and VIKOR (Serbian name for Multicriteria Optimization and Compromise Solution). An illustrative case of selecting the best maintenance method in industrial companies will be developed in the extended version of the paper; here-due to paper limitations-only step C (correlations study with Pearson and Spearman correlations) is demonstrated, with a small example with 3 criteria and seven alternatives.
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