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]
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Many 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.
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Set covering problem solved by new binary firefly algorithm [Problema de Cobertura de Conjunto Resuelto por el Nuevo Algoritmo Luciérnaga Binario] (2020) Crawford B.; Soto R.; Riquelme-Leiva M.; Peña C.; Torres-Rojas C.; Johnson F.; Paredes F. (Institute of Electrical and Electronics Engineers Inc., 2015)
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