Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion
Given that the challenge for evolutionary algorithms when solving many-objective optimization problems lies in balancing the convergence and diversity, a many-objective evolutionary algorithm based on vector angle selection and indicator deletion (MOEA/AS-ID), is proposed. In this algorithm, a coord...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2024-02-01
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| Series: | Jisuanji kexue yu tansuo |
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| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2208111.pdf |
| _version_ | 1797334213377130496 |
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| author | GU Qinghua, LUO Jiale, LI Xuexian |
| author_facet | GU Qinghua, LUO Jiale, LI Xuexian |
| author_sort | GU Qinghua, LUO Jiale, LI Xuexian |
| collection | DOAJ |
| description | Given that the challenge for evolutionary algorithms when solving many-objective optimization problems lies in balancing the convergence and diversity, a many-objective evolutionary algorithm based on vector angle selection and indicator deletion (MOEA/AS-ID), is proposed. In this algorithm, a coordinated mechanism that includes two strategies is designed in the environmental selection process to delete the solutions with poor convergence and diversity one by one, retaining the elitist to participate in the evolution process for the next generation. To be specific, the former strategy based on vector angle selection is used to select a pair of solutions with a similar search direction in the objective space, and the latter indicator-based deletion strategy which uses the [ISDE+] indicator (indicator shift-based density estimation) that takes into account the convergence and diversity of a single solution, is employed to compare the selected pair of solutions and delete the solution with a smaller indicator value, then encourage the population to converge to the Pareto optimal front toward all directions. Finally, the balance between convergence and diversity of the solution set is achieved. On DTLZ (Deb-Thiele-Laumanns-Zitzler), SDTLZ (scaled DTLZ), and MaF (many-objective function) three benchmark test suites with various characteristics，MOEA/AS-ID and six recently proposed many-objective evolutionary algorithms covering all current types perform extensive comparative simulation experiments and numerical results analysis. Simulation results and numerical analysis show that MOEA/AS-ID has strong competitiveness in balancing the convergence and diversity when solving many-objective optimization problems with various characteristics. |
| first_indexed | 2024-03-08T08:17:27Z |
| format | Article |
| id | doaj.art-87ec2dd4ff5043539e7f7035a75b116d |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-03-08T08:17:27Z |
| publishDate | 2024-02-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-87ec2dd4ff5043539e7f7035a75b116d2024-02-02T07:10:08ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182024-02-0118242543810.3778/j.issn.1673-9418.2208111Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator DeletionGU Qinghua, LUO Jiale, LI Xuexian01. School of Management, Xi'an University of Architecture and Technology, Xi'an 710055, China 2. Xi'an Key Laboratory for Intelligent Industrial Perception, Calculation and Decision, Xi'an University of Architec-ture and Technology, Xi'an 710055, China 3. School of Resources Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, ChinaGiven that the challenge for evolutionary algorithms when solving many-objective optimization problems lies in balancing the convergence and diversity, a many-objective evolutionary algorithm based on vector angle selection and indicator deletion (MOEA/AS-ID), is proposed. In this algorithm, a coordinated mechanism that includes two strategies is designed in the environmental selection process to delete the solutions with poor convergence and diversity one by one, retaining the elitist to participate in the evolution process for the next generation. To be specific, the former strategy based on vector angle selection is used to select a pair of solutions with a similar search direction in the objective space, and the latter indicator-based deletion strategy which uses the [ISDE+] indicator (indicator shift-based density estimation) that takes into account the convergence and diversity of a single solution, is employed to compare the selected pair of solutions and delete the solution with a smaller indicator value, then encourage the population to converge to the Pareto optimal front toward all directions. Finally, the balance between convergence and diversity of the solution set is achieved. On DTLZ (Deb-Thiele-Laumanns-Zitzler), SDTLZ (scaled DTLZ), and MaF (many-objective function) three benchmark test suites with various characteristics，MOEA/AS-ID and six recently proposed many-objective evolutionary algorithms covering all current types perform extensive comparative simulation experiments and numerical results analysis. Simulation results and numerical analysis show that MOEA/AS-ID has strong competitiveness in balancing the convergence and diversity when solving many-objective optimization problems with various characteristics.http://fcst.ceaj.org/fileup/1673-9418/PDF/2208111.pdfevolutionary algorithm; many-objective optimization; vector angle selection; indicator deletion; conver-gence; diversity |
| spellingShingle | GU Qinghua, LUO Jiale, LI Xuexian Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion Jisuanji kexue yu tansuo evolutionary algorithm; many-objective optimization; vector angle selection; indicator deletion; conver-gence; diversity |
| title | Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion |
| title_full | Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion |
| title_fullStr | Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion |
| title_full_unstemmed | Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion |
| title_short | Many-Objective Evolutionary Algorithm with Vector Angle Selection and Indicator Deletion |
| title_sort | many objective evolutionary algorithm with vector angle selection and indicator deletion |
| topic | evolutionary algorithm; many-objective optimization; vector angle selection; indicator deletion; conver-gence; diversity |
| url | http://fcst.ceaj.org/fileup/1673-9418/PDF/2208111.pdf |
| work_keys_str_mv | AT guqinghualuojialelixuexian manyobjectiveevolutionaryalgorithmwithvectorangleselectionandindicatordeletion |