An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory
To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by usin...
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| Autor*in: |
Sun, Fuchun [verfasserIn] Chi, Yuhong [author] Wang, Weijun [author] Yu, Chunming [author] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2012 |
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Online-Ressource |
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IGI Global InfoSci Journals Archive 2000 - 2012 |
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| Übergeordnetes Werk: |
In: International journal of software science and computational intelligence - Hershey, Pa : IGI Global, 2009, 4(2012), 2, Seite 1-13 |
| Übergeordnetes Werk: |
volume:4 ; year:2012 ; number:2 ; pages:1-13 |
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10.4018/jssci.2012040101 |
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NLEJ244502064 |
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| 520 | |a To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods | ||
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10.4018/jssci.2012040101 doi (DE-627)NLEJ244502064 (VZGNL)10.4018/jssci.2012040101 DE-627 ger DE-627 rakwb eng Sun, Fuchun verfasserin aut An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory 2012 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods IGI Global InfoSci Journals Archive 2000 - 2012 Boundary Condition Particle Swarm Optimization Quotient Space Search Space Topology Chi, Yuhong author aut Wang, Weijun author aut Yu, Chunming author oth In International journal of software science and computational intelligence Hershey, Pa : IGI Global, 2009 4(2012), 2, Seite 1-13 Online-Ressource (DE-627)NLEJ244419531 (DE-600)2703774-5 1942-9037 nnns volume:4 year:2012 number:2 pages:1-13 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 4 2012 2 1-13 |
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10.4018/jssci.2012040101 doi (DE-627)NLEJ244502064 (VZGNL)10.4018/jssci.2012040101 DE-627 ger DE-627 rakwb eng Sun, Fuchun verfasserin aut An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory 2012 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods IGI Global InfoSci Journals Archive 2000 - 2012 Boundary Condition Particle Swarm Optimization Quotient Space Search Space Topology Chi, Yuhong author aut Wang, Weijun author aut Yu, Chunming author oth In International journal of software science and computational intelligence Hershey, Pa : IGI Global, 2009 4(2012), 2, Seite 1-13 Online-Ressource (DE-627)NLEJ244419531 (DE-600)2703774-5 1942-9037 nnns volume:4 year:2012 number:2 pages:1-13 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 4 2012 2 1-13 |
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10.4018/jssci.2012040101 doi (DE-627)NLEJ244502064 (VZGNL)10.4018/jssci.2012040101 DE-627 ger DE-627 rakwb eng Sun, Fuchun verfasserin aut An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory 2012 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods IGI Global InfoSci Journals Archive 2000 - 2012 Boundary Condition Particle Swarm Optimization Quotient Space Search Space Topology Chi, Yuhong author aut Wang, Weijun author aut Yu, Chunming author oth In International journal of software science and computational intelligence Hershey, Pa : IGI Global, 2009 4(2012), 2, Seite 1-13 Online-Ressource (DE-627)NLEJ244419531 (DE-600)2703774-5 1942-9037 nnns volume:4 year:2012 number:2 pages:1-13 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 4 2012 2 1-13 |
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10.4018/jssci.2012040101 doi (DE-627)NLEJ244502064 (VZGNL)10.4018/jssci.2012040101 DE-627 ger DE-627 rakwb eng Sun, Fuchun verfasserin aut An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory 2012 Online-Ressource nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods IGI Global InfoSci Journals Archive 2000 - 2012 Boundary Condition Particle Swarm Optimization Quotient Space Search Space Topology Chi, Yuhong author aut Wang, Weijun author aut Yu, Chunming author oth In International journal of software science and computational intelligence Hershey, Pa : IGI Global, 2009 4(2012), 2, Seite 1-13 Online-Ressource (DE-627)NLEJ244419531 (DE-600)2703774-5 1942-9037 nnns volume:4 year:2012 number:2 pages:1-13 http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101 X:IGIG Verlag Deutschlandweit zugänglich http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/jssci.2012040101&buylink=true text/html Abstract Deutschlandweit zugänglich ZDB-1-GIS GBV_NL_ARTICLE AR 4 2012 2 1-13 |
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To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods |
| abstractGer |
To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods |
| abstract_unstemmed |
To control the swarm to fly inside the limited search space and deal with the problems of slow search speed and premature convergence in particle swarm optimization algorithm, the authors applied the theory of topology, and proposed a novel quotient space-based boundary condition named QsaBC by using the properties of quotient space and homeomorphism in this paper. In QsaBC, Search space-zoomed factor and Attractor factor are introduced according to analyzing the dynamic behavior and stability of particles, which not only reduce the subjective interference and enforce the capability of global search, but also enhance the power of local search and escaping from an inferior local optimum. Four CEC’2008 benchmark functions were selected to evaluate the performance of QsaBC. Comparative experiments show that QsaBC can get the satisfactory optimization solution with fast convergence speed. Furthermore, QsaBC is more effective to do with errant particles, easier to calculate and has better robustness than other experienced methods |
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An Improved Particle Swarm Optimization Algorithm Based on Quotient Space Theory |
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Chi, Yuhong Wang, Weijun Yu, Chunming |
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Chi, Yuhong Wang, Weijun Yu, Chunming |
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2024-07-06T08:06:36.862Z |
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