A Distributed Parallel Genetic Algorithm oriented adaptive migration strategy

Distributed Parallel Genetic Algorithm is the most widely a parallel genetic algorithm. It has natural parallelism and has high performance in solving complex, large-scale, non-linear, non-differentiable optimization problems. This paper analyzes the traditional limitations of distributed parallel g...

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Vydáno v:2012 8th International Conference on Natural Computation s. 592 - 595
Hlavní autoři: Wei Li, Ying Huang
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.05.2012
Témata:
Adaptive Migration Strategy
Algorithm design and analysis
Computers
Convergence
Distributed Parallel Algorithm
Educational institutions
Function Optimization
Genetic Algorithm
Genetic algorithms
Optimization
Synchronization
ISBN:9781457721304, 1457721309
ISSN:2157-9555
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Shrnutí:Distributed Parallel Genetic Algorithm is the most widely a parallel genetic algorithm. It has natural parallelism and has high performance in solving complex, large-scale, non-linear, non-differentiable optimization problems. This paper analyzes the traditional limitations of distributed parallel genetic algorithms, for its migration fixed blindness and other disadvantages. A Distributed Parallel Genetic Algorithm oriented adaptive migration strategy (AMDPGA) was proposed in this paper, which was suitable for running on the current parallel computers. This Implementation combines the Distributed Parallel Genetic Algorithm and current computer architecture, which makes the Distributed Parallel Genetic Algorithm execute on the mainstream computer concurrently and improve the convergent speed. The experiments showed that this algorithm has not only faster convergent speed but also has more accurate precision and overcome more faults as well as higher parallel efficiency.
ISBN:9781457721304
1457721309
ISSN:2157-9555
DOI:10.1109/ICNC.2012.6234584