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The artificial bee colony (ABC) algorithm, which is inspired by the foraging behavior of honey bees, is one of the swarm intelligence systems. This algorithm can provide an efficient exploration of the optimal solutions using three different types of agents for optimization problems with multimodal functions. However, the performance of the conventional ABC algorithm decreases for high-dimensional problems. In this study, we propose an improved algorithm using the network structure of agents to enhance the ability for global search. The efficacy of the proposed algorithm is evaluated by performing computer experiments with high-dimensional benchmark functions.

Characteristic Analysis of Artificial Bee Colony Algorithm with Network-Structure