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Using binary fruit fly algorithm for solving the set covering problem [Utilizando el Algoritmo binario Fruit Fly para resolver el Problema del Conjunto de Cobertura]

dc.contributor.authorCrawford B.
dc.contributor.authorSoto R.
dc.contributor.authorTorres-Rojas C.
dc.contributor.authorPeña C.
dc.contributor.authorRiquelme-Leiva M.
dc.contributor.authorJohnson F.
dc.contributor.authorParedes F.
dc.date.accessioned2020-09-02T22:16:12Z
dc.date.available2020-09-02T22:16:12Z
dc.date.issued2015
dc.identifier10.1109/CISTI.2015.7170352
dc.identifier.urihttps://hdl.handle.net/20.500.12728/4237
dc.descriptionMany practical applications are used in set covering problems (SCP), in this research, we used to solve SCP: the binary Fruit Fly Optimization algorithms. This algorithm is divided in four phases: initiation, smell based search local vision based search and global vision based search. The metaheuristic is based by the knowledge from the foraging behavior of fruit-flies in finding food. The algorithm used a probability vector to improve the exploration. The tests were performed with eight different transfer functions and an elitist selection method. The test results show the effectiveness of the algorithm proposed. © 2015 AISTI.
dc.language.isoes
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectfruit fly optimization algorithm
dc.subjectmetaheuristics
dc.subjectset covering problem
dc.subjecttransfer functions
dc.subjectBins
dc.subjectFactory automation
dc.subjectFruits
dc.subjectInformation systems
dc.subjectOptimization
dc.subjectTransfer functions
dc.subjectAlgorithm for solving
dc.subjectForaging behaviors
dc.subjectFruit flies
dc.subjectMeta heuristics
dc.subjectMetaheuristic
dc.subjectProbability vector
dc.subjectSelection methods
dc.subjectSet covering problem
dc.subjectAlgorithms
dc.titleUsing binary fruit fly algorithm for solving the set covering problem [Utilizando el Algoritmo binario Fruit Fly para resolver el Problema del Conjunto de Cobertura]
dc.typeConference Paper


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