Efficient Method to find Nearest Neighbours in Flocking Behaviours

Flocking is a behaviour in which objects move or work together as a group. This behaviour is very common in nature think of a flock of flying geese or a school of fish in the sea. Flocking behaviours have been simulated in different areas such as computer animation, graphics and games. However, the simulation of the flocking behaviours of large number of objects in real time is computationally intensive task. This intensity is due to the n-squared complexity of the nearest neighbour (NN) algorithm used to separate objects, where n is the number of objects. This paper proposes an efficient NN method based on the partial distance approach to enhance the performance of the flocking algorithm and its application to flocking behaviour. The proposed method was implemented and the experimental results showed that the proposed method outperformed conventional NN methods when applied to flocking fish.