[b]artificial bee colony abc algorithm in matlab simulink[/b]

Artificial Bee Colony (ABC) Algorithm

Artificial Bee Colony (ABC) is one of the most recently defined algorithms by Derby Karabog in 2005, inspired by the intelligent behavior of honey bee. This particle is similar to herd optimization (PSO) and differential development (DE) algorithms, and uses common control parameters such as colony size and maximum cycle number. ABC provides a population-based search process in which individuals are called food posts, modified by artificial bees over time, and the purpose of the bee is to find places of food sources with high ambrosia. And finally the highest elixir. In ABC system, artificial bees fly in a multi-discovery spot and some (employed and spectacular bees) choose food sources based on the experience of themselves and their close friends, and adjust their position some (scouts) fly And select food sources randomly without using the experience. If the nectar of a new source is more than the previous one in their memory, then they remember the new situation and forget the past one. Thus, the ABC system combines local search methods, which are managed by visitors and scouts, trying to balance the exploration and exploitation process along with the global search practices performed by the bees of the audience.