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About Literature Review
This literature review discusses parallel genetic algorithms (PGAs) and their application to solving inverse kinematics problems. The key points are: 1) PGAs divide the population into multiple subpopulations that evolve independently with occasional migration between subpopulations. This can find high-quality solutions faster than sequential GAs. 2) Literature explores various PGA topologies, migration strategies, and synchronization techniques. Coarse-grained PGAs tend to have higher computation-to-communication ratios than fine-grained ones. 3) The review provides background on applying PGAs to optimization problems and challenges assessing their speedup due to genetic algorithms' stochastic nature. Statistical performance analysis is commonly used.
Detailed Information
| Author: | ['Matthew Ryan'] |
|---|---|
| Publication Year: | 2014 |
| Pages: | 6 |
| Language: | English |
| Format: | |
| Price: | FREE |
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