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dc.contributor.author
González, Begoña  
dc.contributor.author
Rossit, Daniel Alejandro  
dc.contributor.author
Méndez, Máximo  
dc.contributor.author
Frutos, Mariano  
dc.date.available
2023-05-18T12:39:31Z  
dc.date.issued
2022-01  
dc.identifier.citation
González, Begoña; Rossit, Daniel Alejandro; Méndez, Máximo; Frutos, Mariano; Objective space division-based hybrid evolutionary algorithm for handing overlapping solutions in combinatorial problems; American Institute of Mathematical Sciences; Mathematical Biosciences And Engineering; 19; 4; 1-2022; 3369-3401  
dc.identifier.issn
1547-1063  
dc.identifier.uri
http://hdl.handle.net/11336/197965  
dc.description.abstract
Overlapping solutions occur when more than one solution in the space of decisions maps to the same solution in the space of objectives. This situation threatens the exploration capacity of Multi- Objective Evolutionary Algorithms (MOEAs), preventing them from having a good diversity in their population. The influence of overlapping solutions is intensified on multi-objective combinatorial problems with a low number of objectives. This paper presents a hybrid MOEA for handling overlapping solutions that combines the classic NSGA-II with a strategy based on Objective Space Division (OSD). Basically, in each generation of the algorithm, the objective space is divided into several regions using the nadir solution calculated from the current generation solutions. Furthermore, the solutions in each region are classified into non-dominated fronts using different optimization strategies in each of them. This significantly enhances the achieved diversity of the approximate front of non-dominated solutions. The proposed algorithm (called NSGA-II/OSD) is tested on a classic Operations Research problem: The Multi-Objective Knapsack Problem (0-1 MOKP) with two objectives. Classic NSGA-II, MOEA/D and Global WASF-GA are used to compare the performance of NSGA-II/OSD. In the case of MOEA/D two different versions are implemented, each of them with a different strategy for specifying the reference point. These MOEA/D reference point strategies are thoroughly studied and new insights are provided. This paper analyses in depth the impact of overlapping solutions on MOEAs, studying the number of overlapping solutions, the number of solution repairs, the hypervolume metric, the attainment surfaces and the approximation to the real Pareto front, for different sizes of 0-1 MOKPs with two objectives. The proposed method offers very good performance when compared to the classic NSGA-II, MOEA/D and Global WASF-GA algorithms, all of them well-known in the literature.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Institute of Mathematical Sciences  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
BI-OBJECTIVE KNAPSACK PROBLEM  
dc.subject
MULTI-OBJECTIVE COMBINATORIAL OPTIMIZATION PROBLEMS  
dc.subject
MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS  
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OBJECTIVE SPACE DIVISION  
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OVERLAPPING SOLUTIONS  
dc.subject.classification
Otras Ingenierías y Tecnologías  
dc.subject.classification
Otras Ingenierías y Tecnologías  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Objective space division-based hybrid evolutionary algorithm for handing overlapping solutions in combinatorial problems  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-05-11T17:45:41Z  
dc.identifier.eissn
1551-0018  
dc.journal.volume
19  
dc.journal.number
4  
dc.journal.pagination
3369-3401  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
Springfield  
dc.description.fil
Fil: González, Begoña. Universidad de Las Palmas de Gran Canaria; España  
dc.description.fil
Fil: Rossit, Daniel Alejandro. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina  
dc.description.fil
Fil: Méndez, Máximo. Universidad de Las Palmas de Gran Canaria; España  
dc.description.fil
Fil: Frutos, Mariano. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentina  
dc.journal.title
Mathematical Biosciences And Engineering  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/http://www.aimspress.com/article/doi/10.3934/mbe.2022156  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.3934/mbe.2022156