ABC (Artificial Bee Colony) Algorithm – Part 1

ABC (Artificial Bee Colony) Algorithm – Part 1
By: Mei Jianhong (PhD Student)

As an SI (swarm intelligence), ABC (Artificial Bee Colony) model is first proposed by Tereshko and Loengarov in 2005, which is inspired from foraging behavior of honey bees. Thereafter, Karaboga (2005) developed the ABC algorithm to optimize numerical problems. The honey bees work according to their different division of labor, and share the food sources information to get the optimal solution of problem. There are three components in ABC model, employed and unemployed foraging bees, and food sources.

There are two groups of unemployed bees, onlookers and scouts. At first, the employed bees are associated with the specific food sources, and then onlookers watch the dancing of employed bees in the hive to obtain the food sources information and determine a food source. The scout bees are in charge of searching for food sources randomly. The employed bees and onlookers keep exploiting the nectar of food sources till the food sources are exhausted. Then, the employed bee which was exploiting the exhausted food source becomes a scout bee to search a new food sources in the neighborhood. The positions of the food sources represent the possible solutions of the problem and the nectar amount of a food source means the fitness of the associated solution. Thus, the number of employed bees is equal to the number of food sources and they are one-to-one associated. The general flow chart of ABC algorithm is shown below:


  2. Karaboga, D., Gorkemli, B., Ozturk, C., & Karaboga, N. (2014). A comprehensive survey: artificial bee colony (ABC) algorithm and applications. Artificial Intelligence Review42(1), 21-57.