LAPSE:2023.10618
Published Article
LAPSE:2023.10618
Class Thresholds Pre-Definition by Clustering Techniques for Applications of ELECTRE TRI Method
February 27, 2023
Abstract
The sorting problem in the Multi-criteria Decision Analysis (MCDA) has been used to address issues whose solutions involve the allocation of alternatives in classes. Traditional multi-criteria methods are commonly used for this task, such as ELECTRE TRI, AHP-Sort, UTADIS, PROMETHEE, GAYA, etc. While using these approaches to perform the sorting procedure, the decision-makers define profiles (thresholds) for classes to compare the alternatives within these profiles. However, most such applications are based on subjective tasks, i.e., decision-makers’ expertise, which sometimes might be imprecise. To fill that gap, in this paper, a comparative analysis using the multi-criteria method ELECTRE TRI and clustering algorithms is performed to obtain an auxiliary procedure to define initial thresholds for the ELECTRE TRI method. In this proposed methodology, K-Means, K-Medoids, Fuzzy C-Means algorithms, and Bio-Inspired metaheuristics such as PSO, Differential Evolution, and Genetic algorithm for clustering are tested considering a dataset from a fundamental problem of sorting in Water Distribution Networks. The computational performances indicate that Fuzzy C-Means was more suitable for achieving the desired response. The practical contributions show a relevant procedure to provide an initial view of boundaries in multi-criteria sorting methods based on the datasets from specific applications. Theoretically, it is a new development to pre-define the initial limits of classes for the sorting problem in multi-criteria approach.
The sorting problem in the Multi-criteria Decision Analysis (MCDA) has been used to address issues whose solutions involve the allocation of alternatives in classes. Traditional multi-criteria methods are commonly used for this task, such as ELECTRE TRI, AHP-Sort, UTADIS, PROMETHEE, GAYA, etc. While using these approaches to perform the sorting procedure, the decision-makers define profiles (thresholds) for classes to compare the alternatives within these profiles. However, most such applications are based on subjective tasks, i.e., decision-makers’ expertise, which sometimes might be imprecise. To fill that gap, in this paper, a comparative analysis using the multi-criteria method ELECTRE TRI and clustering algorithms is performed to obtain an auxiliary procedure to define initial thresholds for the ELECTRE TRI method. In this proposed methodology, K-Means, K-Medoids, Fuzzy C-Means algorithms, and Bio-Inspired metaheuristics such as PSO, Differential Evolution, and Genetic algorithm for clustering are tested considering a dataset from a fundamental problem of sorting in Water Distribution Networks. The computational performances indicate that Fuzzy C-Means was more suitable for achieving the desired response. The practical contributions show a relevant procedure to provide an initial view of boundaries in multi-criteria sorting methods based on the datasets from specific applications. Theoretically, it is a new development to pre-define the initial limits of classes for the sorting problem in multi-criteria approach.
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Keywords
class bounds and variations, clustering algorithms, multi-criteria sorting methods, multi-criteria sorting procedure
Subject
Suggested Citation
Trojan F, Fernandez PIR, Guerreiro M, Biuk L, Mohamed MA, Siano P, Filho RFD, Marinho MHN, Siqueira HV. Class Thresholds Pre-Definition by Clustering Techniques for Applications of ELECTRE TRI Method. (2023). LAPSE:2023.10618
Author Affiliations
Trojan F: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil [ORCID]
Fernandez PIR: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil [ORCID]
Guerreiro M: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil [ORCID]
Biuk L: Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil
Mohamed MA: Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia 61519, Egypt [ORCID]
Siano P: Department of Management & Innovation Systems, University of Salerno, 84084 Fisciano, Italy; Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Filho RFD: Polytechnic School of Pernambuco, University of Pernambuco, R. Benfica 455, Recife 50720-001, PE, Brazil [ORCID]
Marinho MHN: Polytechnic School of Pernambuco, University of Pernambuco, R. Benfica 455, Recife 50720-001, PE, Brazil [ORCID]
Siqueira HV: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil; Graduate Program in Electrical Engineering (PPGEE), Federal U [ORCID]
Fernandez PIR: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil [ORCID]
Guerreiro M: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil [ORCID]
Biuk L: Graduate Program in Electrical Engineering (PPGEE), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil
Mohamed MA: Department of Electrical Engineering, Faculty of Engineering, Minia University, Minia 61519, Egypt [ORCID]
Siano P: Department of Management & Innovation Systems, University of Salerno, 84084 Fisciano, Italy; Department of Electrical and Electronic Engineering Science, University of Johannesburg, Johannesburg 2006, South Africa [ORCID]
Filho RFD: Polytechnic School of Pernambuco, University of Pernambuco, R. Benfica 455, Recife 50720-001, PE, Brazil [ORCID]
Marinho MHN: Polytechnic School of Pernambuco, University of Pernambuco, R. Benfica 455, Recife 50720-001, PE, Brazil [ORCID]
Siqueira HV: Graduate Program in Industrial Engineering (PPGEP), Federal University of Technology-Paraná-UTFPR, R. Doutor Washington Subtil Chueire, 330-Jardim Carvalho, Ponta Grossa 84017-220, PR, Brazil; Graduate Program in Electrical Engineering (PPGEE), Federal U [ORCID]
Journal Name
Energies
Volume
16
Issue
4
First Page
1936
Year
2023
Publication Date
2023-02-15
ISSN
1996-1073
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Original Submission
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PII: en16041936, Publication Type: Journal Article
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LAPSE:2023.10618
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https://doi.org/10.3390/en16041936
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