Coevolutionary Algorithm Applied to Skip Reentry Trajectory Optimization Design
Autor: | Feng Bo Wang, Chang Hong Dong |
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Rok vydání: | 2013 |
Předmět: |
education.field_of_study
Mathematical optimization Meta-optimization Computer Science::Neural and Evolutionary Computation Population Particle swarm optimization General Medicine Trajectory optimization Position (vector) Differential evolution Convergence (routing) Multi-swarm optimization education Algorithm Mathematics |
Zdroj: | Applied Mechanics and Materials. :1424-1431 |
ISSN: | 1662-7482 |
DOI: | 10.4028/www.scientific.net/amm.427-429.1424 |
Popis: | This paper proposed a coevolutionary algorithm combining improved particle swarm optimization algorithm with differential evolution method and its application was provided. Adaptive position escapable mechanism is introduced in the particle swarm optimization to improve the diversity of population and guarantee to achieve the global optima. The differential algorithm is employed in a cooperative manner to maintain the characteristic of fast convergence speed in the later convergence phase. The coevolutionary algorithm is then applied to skip trajectory optimization design for crew exploration vehicle with low-lift-to-drag and several comparative cases are conducted, Results show that coevolutionary algorithm is quite effective in finding the global optimal solution with great accuracy. |
Databáze: | OpenAIRE |
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