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dc.contributor.authorZitouni, Farouq-
dc.contributor.authorHarous, Saad-
dc.contributor.authorMaamri, Ramdane-
dc.date.accessioned2019-06-19T10:06:17Z-
dc.date.available2019-06-19T10:06:17Z-
dc.date.issued2019-03-05-
dc.identifier.urihttp://dspace.univ-ouargla.dz/jspui/handle/123456789/20870-
dc.descriptionLe 2eme Conference Internationale sur intelligence Artificielle et les Technologies Information ICAIIT 2019en_US
dc.description.abstractThe Multi-Robot Task Allocation problem of is the situation where we have a set of tasks and a number of robots, and each task have to be assigned to the appropriate robots that optimize some criteria, e.g. allocate the maximum number of tasks. We present an effective solution to address this problem. It implements a two-stage methodology: first, a global allocation using firefly algorithm, then a local allocation combining artificial bee colony optimization and quantum genetic algorithms. Experimental results show the effectiveness of the proposed solution in terms of the number of allocated tasks and the allocation time.en_US
dc.language.isoenen_US
dc.publisherUniversité Kasdi Merbah Ouarglaen_US
dc.relation.ispartofseries2019;-
dc.subjectMulti-Robot Systemen_US
dc.subjectTask Allocationen_US
dc.subjectFirefly Algorithmen_US
dc.subjectArtificial Bee Colony Optimizationen_US
dc.subjectQuantum Genetic Algorithmsen_US
dc.titleSolving the Multi-Robot Task Allocation Problem using Firefly, Artificial Bee Colony and Quantum Genetic Algorithmsen_US
dc.typeArticleen_US
Appears in Collections:2. Faculté des nouvelles technologies de l’information et de la communication

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