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220822 ||| eng |
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|a 9781839681776
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|a 9781839681769
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| 020 |
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|a intechopen.91586
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|a 9781839681783
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| 100 |
1 |
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|a Soofastaei, Ali
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| 245 |
0 |
0 |
|a The Application of Ant Colony Optimization
|h Elektronische Ressource
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| 260 |
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|b IntechOpen
|c 2022
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| 300 |
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|a 1 electronic resource (90 p.)
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| 653 |
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|a Algorithms and data structures / bicssc
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| 653 |
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|a Algorithms & data structures
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| 700 |
1 |
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|a Soofastaei, Ali
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by/3.0/
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| 024 |
8 |
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|a 10.5772/intechopen.91586
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| 856 |
4 |
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|u https://mts.intechopen.com/storage/books/10400/authors_book/authors_book.pdf
|7 0
|x Verlag
|3 Volltext
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/90292
|z DOAB: description of the publication
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| 520 |
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|a The application of advanced analytics in science and technology is rapidly expanding, and developing optimization technics is critical to this expansion. Instead of relying on dated procedures, researchers can reap greater rewards by utilizing cutting-edge optimization techniques like population-based metaheuristic models, which can quickly generate a solution with acceptable quality. Ant Colony Optimization (ACO) is one the most critical and widely used models among heuristics and meta-heuristics. This book discusses ACO applications in Hybrid Electric Vehicles (HEVs), multi-robot systems, wireless multi-hop networks, and preventive, predictive maintenance.
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