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dc.contributor.editorOstfeld, Avi
dc.date.accessioned2021-04-20T15:05:07Z
dc.date.available2021-04-20T15:05:07Z
dc.date.issued2011
dc.identifierONIX_20210420_9789533071572_280
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/64924
dc.description.abstractAnts communicate information by leaving pheromone tracks. A moving ant leaves, in varying quantities, some pheromone on the ground to mark its way. While an isolated ant moves essentially at random, an ant encountering a previously laid trail is able to detect it and decide with high probability to follow it, thus reinforcing the track with its own pheromone. The collective behavior that emerges is thus a positive feedback: where the more the ants following a track, the more attractive that track becomes for being followed; thus the probability with which an ant chooses a path increases with the number of ants that previously chose the same path. This elementary ant's behavior inspired the development of ant colony optimization by Marco Dorigo in 1992, constructing a meta-heuristic stochastic combinatorial computational methodology belonging to a family of related meta-heuristic methods such as simulated annealing, Tabu search and genetic algorithms. This book covers in twenty chapters state of the art methods and applications of utilizing ant colony optimization algorithms. New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science applications from transportation, water resources, electrical and computer science disciplines are presented.
dc.languageEnglish
dc.subject.classificationbic Book Industry Communication::U Computing & information technology::UY Computer science::UYQ Artificial intelligenceen_US
dc.subject.otherNeural networks & fuzzy systems
dc.titleAnt Colony Optimization
dc.title.alternativeMethods and Applications
dc.typebook
oapen.identifier.doi10.5772/577
oapen.relation.isPublishedBy78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6
oapen.relation.isbn9789533071572
oapen.relation.isbn9789535159803
oapen.imprintIntechOpen
oapen.pages354


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