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Titolo: |
Application of Ant Colony Optimization / / edited by Ali Soofastaei
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Pubblicazione: | London : , : IntechOpen, , 2022 |
©2022 | |
Descrizione fisica: | 1 online resource (xi, 90 pages) : illustrations |
Disciplina: | 511.8 |
Soggetto topico: | Mathematical models |
Ant algorithms | |
Persona (resp. second.): | SoofastaeiAli |
Nota di bibliografia: | Includes bibliographical references. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Application of Ant Colony Optimization ![]() |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910688237603321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |