earticle

영어

Aiming at such shortcomings of traditional Bat algorithm as low precision convergence, premature convergence, slow convergence, an improved BA based on inertia weight factor and Lévy flight (ILBA) has been proposed, which has made two modifications on update equations of bat flying position in BA, using inertia weight factor to keep the flight inertia of bat individual, adaptively adjust the exploitation mechanism of the algorithm in different iteration periods, make the algorithm achieve better convergence precision and altering the strategy about position update of bats from Brownian random walks into Lévy flights strategy to effectively avoid local optimism of the algorithm and guarantee its exploration mechanism while taking advantage of heavy-tailed effect of Lévy flight to speed up the convergence. By means of 4 typical test functions simulation, the results show that ILBA boasts faster convergence and superior optimal performance compared to traditional BA and LBA.