Artificial Flora (AF) Optimization Algorithm

The swarm intelligence algorithm has characteristics of self-organization, robustness, coordination, simplicity, distribution and extensibility. [...]the swarm intelligence optimization algorithms are widely used in parameter estimation [12], automatic control [13], machine manufacturing [14], pattern recognition [15], transportation engineering [16], and so on. Because of climate change, severe natural environment, or competition, the distribution area of flora can be expanded, reduced, or migrated. Rule 1: Because of a sudden change in the environment or some kind of artificial action, a species may be randomly distributed in a region where there is no such species and then become the most primitive original plant. According to Rule 1, there was no such species in the region, due to sudden environmental changes or some kind of artificial action, original plants were spread over a random location in the region, as the ◇(x1) shows in Figure 1.