Bare Bones Particle Swarms With Linear Variable Weight

In order to improve the ability of BBPSO to jump out of the local optimal solution and avoid it falling into the local optimal solution, this paper proposes the BBPSO with linear variable weights. First, a linearly changing adjustment factor β is introduced into the iterative formula to balance the exploration and exploitation. Secondly, the scale factor D is introduced for the fast convergence of BBPSO, so that the adjustment factor will decrease to its minimum in the first half of the iterative process. The experimental results show that BBPSO with linear variable weight has better global optimality and can effectively balance the exploration and exploitation.