A Multi-Species Artificial Bee Colony Algorithm and Its Application for Crowd Simulation

The artificial bee colony (ABC) algorithm has the problem of slow convergence and may be trapped into local optimum. In this paper, a multi-species ABC (MABC) algorithm is proposed based on the multi-swarm model. The MABC algorithm uses dynamic segmentation of the swarm and a co-evolution strategy. The strategy of dynamic segmentation divides the colony into multiple sub-species, and the species communicate with each other using the co-evolution strategy. The combined global communication pattern and local communication pattern are applied among sub-species. In order to test the performance of the algorithm, experiments are conducted on the CEC’05 Test Functions. To test the performance of the algorithm in crowd simulation for evacuation, we simulate it through a crowd simulation system for evacuation, and the MABC algorithm improves the efficiency of crowd evacuation.