The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm
Effectively combining various evolutionary computing algorithms and leveraging the advantages of each can significantly enhance the convergence speed and solution quality of the algorithm. However, a mere combination of evolutionary computing algorithms may not comprehensively improve optimization p...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10496134/ |
| _version_ | 1797206091669438464 |
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| author | Yongjian Yang Youwei Deng Bingsong Xiao Xiaohong Zhao |
| author_facet | Yongjian Yang Youwei Deng Bingsong Xiao Xiaohong Zhao |
| author_sort | Yongjian Yang |
| collection | DOAJ |
| description | Effectively combining various evolutionary computing algorithms and leveraging the advantages of each can significantly enhance the convergence speed and solution quality of the algorithm. However, a mere combination of evolutionary computing algorithms may not comprehensively improve optimization performance and may even lead to poorer performance in certain optimization problems. The aim of the paper is to provide a fundamental integrating platform and method based on species explode and deracinate algorithm. Utilizing the species explode and deracinate algorithm as a foundation, this study presents a hybrid algorithm named SED-PSO algorithm by utilizing the particle swarm optimization algorithm as an exemplar. The outcomes of the simulations conducted on 27 benchmark functions published by the Competition on Evolutionary Constrained demonstrate that the SED-PSO algorithm exhibits exceptional convergence accuracy, robust stability, and rapid convergence speed. The simulation results comprehensively illustrate that the species explode and deracinate algorithm serves as a fundamental integrating platform for diverse evolutionary computing algorithms, while also incorporating the strengths of each algorithm. Additionally, the outcomes of the optimization of sensor network coverage reveal that the SED-PSO algorithm exhibits superior solution quality, minimal occurrence of local extremum, and enhanced stability and efficacy. |
| first_indexed | 2024-04-24T09:01:30Z |
| format | Article |
| id | doaj.art-1f04c49e6064464f9bb6963d5d00bbbf |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-24T09:01:30Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1f04c49e6064464f9bb6963d5d00bbbf2024-04-15T23:01:01ZengIEEEIEEE Access2169-35362024-01-0112524395245110.1109/ACCESS.2024.338730810496134The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization AlgorithmYongjian Yang0https://orcid.org/0000-0003-4165-7415Youwei Deng1Bingsong Xiao2Xiaohong Zhao3Aviation Engineering School, Air Force Engineering University, Xi’an, ChinaAviation Engineering School, Air Force Engineering University, Xi’an, ChinaAviation Engineering School, Air Force Engineering University, Xi’an, ChinaAviation Engineering School, Air Force Engineering University, Xi’an, ChinaEffectively combining various evolutionary computing algorithms and leveraging the advantages of each can significantly enhance the convergence speed and solution quality of the algorithm. However, a mere combination of evolutionary computing algorithms may not comprehensively improve optimization performance and may even lead to poorer performance in certain optimization problems. The aim of the paper is to provide a fundamental integrating platform and method based on species explode and deracinate algorithm. Utilizing the species explode and deracinate algorithm as a foundation, this study presents a hybrid algorithm named SED-PSO algorithm by utilizing the particle swarm optimization algorithm as an exemplar. The outcomes of the simulations conducted on 27 benchmark functions published by the Competition on Evolutionary Constrained demonstrate that the SED-PSO algorithm exhibits exceptional convergence accuracy, robust stability, and rapid convergence speed. The simulation results comprehensively illustrate that the species explode and deracinate algorithm serves as a fundamental integrating platform for diverse evolutionary computing algorithms, while also incorporating the strengths of each algorithm. Additionally, the outcomes of the optimization of sensor network coverage reveal that the SED-PSO algorithm exhibits superior solution quality, minimal occurrence of local extremum, and enhanced stability and efficacy.https://ieeexplore.ieee.org/document/10496134/Evolutionary computing algorithmspecies explode and deracinate algorithmparticle swarm optimization algorithmcompetition on evolutionary constrainedoptimization of sensor network coverage |
| spellingShingle | Yongjian Yang Youwei Deng Bingsong Xiao Xiaohong Zhao The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm IEEE Access Evolutionary computing algorithm species explode and deracinate algorithm particle swarm optimization algorithm competition on evolutionary constrained optimization of sensor network coverage |
| title | The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm |
| title_full | The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm |
| title_fullStr | The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm |
| title_full_unstemmed | The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm |
| title_short | The Method to Integrate Species Explode and Deracinate Algorithm With Particle Swarm Optimization Algorithm |
| title_sort | method to integrate species explode and deracinate algorithm with particle swarm optimization algorithm |
| topic | Evolutionary computing algorithm species explode and deracinate algorithm particle swarm optimization algorithm competition on evolutionary constrained optimization of sensor network coverage |
| url | https://ieeexplore.ieee.org/document/10496134/ |
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