Abstract:

We proposed an improved shuffled frog leaping algorithm based on cellular automaton theory. In the algorithm, the cellular automaton was embedded into the shuffled frog leaping algorithm to improve the grouping strategy. We used cloud model and chaos theory to improve the individual update mode, and used dynamic characteristics of biological evolution to simulate the evolution rules. Simulation results of the six kinds of basic test functions show that the algorithm has better convergence precision and computing speed, and it is suitable for multi peak function optimization.

Key words: shuffled flog leaping algorithm, cellular automaton, cloud model, chaos, continuous space optimization