Using low-power platforms for Evolutionary Multi-Objective Optimization algorithms
Nowadays, the application of Evolutionary Multi-Objective Optimization (EMO) algorithms in real-time systems receives considerable interest. In this context, the energy efficiency of computational systems is of paramount relevance. Recently, the use of embedded systems based on heterogeneous (CPU + ...
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| Published in: | The Journal of supercomputing Vol. 73; no. 1; pp. 302 - 315 |
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| Main Authors: | , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Springer US
01.01.2017
Springer Nature B.V |
| Subjects: | |
| ISSN: | 0920-8542, 1573-0484 |
| Online Access: | Get full text |
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