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A bumble bees mating optimization algorithm for global unconstrained optimization problems

Marinakis Ioannis, Matsatsinis Nikolaos, Marinaki Magdalini

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/65E8F3E9-92B4-4790-9972-926EB6E5ED7F
Έτος 2010
Τύπος Περίληψη Δημοσίευσης σε Συνέδριο
Άδεια Χρήσης
Λεπτομέρειες
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
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Περίληψη

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.

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