Το έργο με τίτλο A bumble bees mating optimization algorithm for global unconstrained optimization problems από τον/τους δημιουργό/ούς Marinakis Ioannis, Matsatsinis Nikolaos, Marinaki Magdalini διατίθεται με την άδεια Creative Commons Αναφορά Δημιουργού 4.0 Διεθνές
Βιβλιογραφική Αναφορά
Y. Marinakis, M. Marinaki and N. Matsatsinis, “A Bumble bees mating optimization algorithm for global unconstrained optimization problems”, in Nature Inspired Cooperative Strategies for Optimization, Studies in Computational Intelligence, 2010, pp. 305-318. doi: 10.1007/978-3-642-12538-6_26
https://doi.org/10.1007/978-3-642-12538-6_26
A new nature inspired algorithm, that simulates the mating behavior of the bumble bees, the Bumble Bees Mating Optimization (BBMO) algorithm, is presented in this paper for solving global unconstrained optimization problems. The performance of the algorithm is compared with other popular metaheuristic and nature inspired methods when applied to the most classic global unconstrained optimization problems. The methods used for comparisons are Genetic Algorithms, Island Genetic Algorithms, Differential Evolution, Particle Swarm Optimization, and the Honey Bees Mating Optimization algorithm. A high performance of the proposed algorithm is achieved based on the results obtained.