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100   $a20230704d2022      uy             0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 00$aApplication of Ant Colony Optimization /$fedited by Ali Soofastaei
210  1$aLondon :$cIntechOpen,$d2022.
210  4$dİ2022
215   $a1 online resource (xi, 90 pages) $cillustrations
311   $a1-83968-178-0 
320   $aIncludes bibliographical references.
330   $aThe 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.
606   $aMathematical models
606   $aAnt algorithms
615  0$aMathematical models.
615  0$aAnt algorithms.
676   $a511.8
702   $aSoofastaei$b Ali
801  0$bNjHacI
801  1$bNjHacl
906   $aBOOK
912   $a9910688237603321
996   $aApplication of Ant Colony Optimization$93122469
997   $aUNINA