Abstract An optimization algorithm is proposed based on the simulation of flight modes of the real birds, namely particle swarm optimization algorithm with double-flight modes(DMPSO). Particles can use maneuver flight-mode or non-maneuver flight-mode to fly during searching. Each particle chooses its flight-mode according to the feedback of the swarm information and its own state in the search. To test the performance of DMPSO, experiments are carried out on some typical complex high-dimensional optimization problems. The experimental results show that the DMPSO avoids the premature convergence problems and it is effective when solving complex high dimensional optimization problems.
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2014, Vol. 27 
