Non-inertial opposition-based particle swarm optimization with adaptive elite mutation
Non-inertia1 opposition-based partic1e swarm optimization with adaptive e1ite mutation（NOPSO）was proposed to overcome the drawbacks，such as，s1ow convergence speed，fa11ing into 1oca1 optimization，of opposition-based partic1e swarm optimization.In addition to increasing the diversity of popu1ation，two...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2017-08-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017165/ |
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| author | Lan-lan KANG Wen-yong DONG Wan-juan SONG Kang-shun LI |
| author_facet | Lan-lan KANG Wen-yong DONG Wan-juan SONG Kang-shun LI |
| author_sort | Lan-lan KANG |
| collection | DOAJ |
| description | Non-inertia1 opposition-based partic1e swarm optimization with adaptive e1ite mutation（NOPSO）was proposed to overcome the drawbacks，such as，s1ow convergence speed，fa11ing into 1oca1 optimization，of opposition-based partic1e swarm optimization.In addition to increasing the diversity of popu1ation，two mechanisms were introduced to ba1ance the contradiction between exp1oration and exp1oitation during its iterations process.The first one was non-inertia1 ve1ocity（NIV）equation，which aimed to acce1erate the process of convergence of the a1gorithm via better access to and use of environmenta1 information.The second one was adaptive e1ite mutation strategy（AEM），which aimed to avoid trap into 1oca1 optimum.Experimenta1 resu1ts show NOPSO a1gorithm has stronger competitive abi1ity compared with opposition-based partic1e swarm optimizations and its varieties in both ca1cu1ation accuracy and computation cost. |
| format | Article |
| id | doaj-art-e7f51646e57547c7b3c584248ceb7392 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2017-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-e7f51646e57547c7b3c584248ceb73922025-01-14T07:12:45ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2017-08-0138667859711454Non-inertial opposition-based particle swarm optimization with adaptive elite mutationLan-lan KANGWen-yong DONGWan-juan SONGKang-shun LINon-inertia1 opposition-based partic1e swarm optimization with adaptive e1ite mutation（NOPSO）was proposed to overcome the drawbacks，such as，s1ow convergence speed，fa11ing into 1oca1 optimization，of opposition-based partic1e swarm optimization.In addition to increasing the diversity of popu1ation，two mechanisms were introduced to ba1ance the contradiction between exp1oration and exp1oitation during its iterations process.The first one was non-inertia1 ve1ocity（NIV）equation，which aimed to acce1erate the process of convergence of the a1gorithm via better access to and use of environmenta1 information.The second one was adaptive e1ite mutation strategy（AEM），which aimed to avoid trap into 1oca1 optimum.Experimenta1 resu1ts show NOPSO a1gorithm has stronger competitive abi1ity compared with opposition-based partic1e swarm optimizations and its varieties in both ca1cu1ation accuracy and computation cost.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017165/non-inertia1 ve1ocity equationgenera1ized opposition-based 1earningadaptive e1ite mutationpartic1e swarm optimization |
| spellingShingle | Lan-lan KANG Wen-yong DONG Wan-juan SONG Kang-shun LI Non-inertial opposition-based particle swarm optimization with adaptive elite mutation Tongxin xuebao non-inertia1 ve1ocity equation genera1ized opposition-based 1earning adaptive e1ite mutation partic1e swarm optimization |
| title | Non-inertial opposition-based particle swarm optimization with adaptive elite mutation |
| title_full | Non-inertial opposition-based particle swarm optimization with adaptive elite mutation |
| title_fullStr | Non-inertial opposition-based particle swarm optimization with adaptive elite mutation |
| title_full_unstemmed | Non-inertial opposition-based particle swarm optimization with adaptive elite mutation |
| title_short | Non-inertial opposition-based particle swarm optimization with adaptive elite mutation |
| title_sort | non inertial opposition based particle swarm optimization with adaptive elite mutation |
| topic | non-inertia1 ve1ocity equation genera1ized opposition-based 1earning adaptive e1ite mutation partic1e swarm optimization |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2017165/ |
| work_keys_str_mv | AT lanlankang noninertialoppositionbasedparticleswarmoptimizationwithadaptiveelitemutation AT wenyongdong noninertialoppositionbasedparticleswarmoptimizationwithadaptiveelitemutation AT wanjuansong noninertialoppositionbasedparticleswarmoptimizationwithadaptiveelitemutation AT kangshunli noninertialoppositionbasedparticleswarmoptimizationwithadaptiveelitemutation |