New Heuristic Method Based on Evolution of Random Points to the Pareto Frontier for Bi-objective Optimization Problems.
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| Title: | New Heuristic Method Based on Evolution of Random Points to the Pareto Frontier for Bi-objective Optimization Problems. |
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| Authors: | Martinez, André Luís Machado1 martinez@utfpr.edu.br, Martinez, Cristiane Aparecida Pendeza2 crismartinez@utfpr.edu.br, Castelani, Emerson Vitor3 evcastelani@uem.br |
| Source: | IAENG International Journal of Applied Mathematics. Apr2025, Vol. 55 Issue 4, p711-719. 9p. |
| Subjects: | Code division multiple access, Particle swarm optimization, Telecommunication systems, Energy consumption, Point set theory |
| Abstract: | We introduce a Pareto dominance-based heuristic designed to address bi-objective optimization problems by tracing the evolution from a random point to the Pareto frontier. The heuristic consists of three main steps. First, a feasible random approximation for the bi-objective problem is established. Next, this point evolves towards the optimal objectives and the Pareto frontier, leveraging trust regions around each approximation. Additionally, at specific iteration intervals, the current approximations optimizing the objectives are integrated as new approximations to the Pareto frontier, enriching the set of points along the frontier. This process iterates until convergence is reached. We would also like to propose an enhanced version of this method, which includes multiple initial points while maintaining the original method's structure. In this work, we compare the performance of the classic Weighted Sum (WS) method with both the EORP and the improved EMRP methods for solving the energy efficiency (EE) and spectral efficiency (SE) trade-off in optical code division multiple access (OCDMA) communication systems. The WS method is examined in two variants: one combined with the Hill Climbing heuristic (WS-HC) and the other with the Particle Swarm Optimization heuristic (WS-PSO). [ABSTRACT FROM AUTHOR] |
| Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 184179876 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: New Heuristic Method Based on Evolution of Random Points to the Pareto Frontier for Bi-objective Optimization Problems. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Martinez%2C+André+Luís+Machado%22">Martinez, André Luís Machado</searchLink><relatesTo>1</relatesTo><i> martinez@utfpr.edu.br</i><br /><searchLink fieldCode="AR" term="%22Martinez%2C+Cristiane+Aparecida+Pendeza%22">Martinez, Cristiane Aparecida Pendeza</searchLink><relatesTo>2</relatesTo><i> crismartinez@utfpr.edu.br</i><br /><searchLink fieldCode="AR" term="%22Castelani%2C+Emerson+Vitor%22">Castelani, Emerson Vitor</searchLink><relatesTo>3</relatesTo><i> evcastelani@uem.br</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22IAENG+International+Journal+of+Applied+Mathematics%22">IAENG International Journal of Applied Mathematics</searchLink>. Apr2025, Vol. 55 Issue 4, p711-719. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Code+division+multiple+access%22">Code division multiple access</searchLink><br /><searchLink fieldCode="DE" term="%22Particle+swarm+optimization%22">Particle swarm optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication+systems%22">Telecommunication systems</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Point+set+theory%22">Point set theory</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We introduce a Pareto dominance-based heuristic designed to address bi-objective optimization problems by tracing the evolution from a random point to the Pareto frontier. The heuristic consists of three main steps. First, a feasible random approximation for the bi-objective problem is established. Next, this point evolves towards the optimal objectives and the Pareto frontier, leveraging trust regions around each approximation. Additionally, at specific iteration intervals, the current approximations optimizing the objectives are integrated as new approximations to the Pareto frontier, enriching the set of points along the frontier. This process iterates until convergence is reached. We would also like to propose an enhanced version of this method, which includes multiple initial points while maintaining the original method's structure. In this work, we compare the performance of the classic Weighted Sum (WS) method with both the EORP and the improved EMRP methods for solving the energy efficiency (EE) and spectral efficiency (SE) trade-off in optical code division multiple access (OCDMA) communication systems. The WS method is examined in two variants: one combined with the Hill Climbing heuristic (WS-HC) and the other with the Particle Swarm Optimization heuristic (WS-PSO). [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of IAENG International Journal of Applied Mathematics is the property of International Association of Engineers (IAENG) and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 711 Subjects: – SubjectFull: Code division multiple access Type: general – SubjectFull: Particle swarm optimization Type: general – SubjectFull: Telecommunication systems Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Point set theory Type: general Titles: – TitleFull: New Heuristic Method Based on Evolution of Random Points to the Pareto Frontier for Bi-objective Optimization Problems. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Martinez, André Luís Machado – PersonEntity: Name: NameFull: Martinez, Cristiane Aparecida Pendeza – PersonEntity: Name: NameFull: Castelani, Emerson Vitor IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 19929978 Numbering: – Type: volume Value: 55 – Type: issue Value: 4 Titles: – TitleFull: IAENG International Journal of Applied Mathematics Type: main |
| ResultId | 1 |
