当C时，采用式(13)更新下一代，当B 时，采用式(16)跟新下一代位

When C, use equation (13) to update the next generation, when B, use equation (16) to follow the new next generation position. However, at this stage, the whale algorithm is easy to fall into local optimality, which leads to relatively low accuracy. Therefore, this article improves the position update formula by introducing inertial weights. The expression of inertial weights is expressed as follows:

When C, adoption (13) updates the next generation, and when B, adopts (16) with the new next generation position. However, at this stage the whale algorithm is prone to local optimal, resulting in relatively low accuracy, so this paper introduces inertial weights to improve the position update formula, inertial weight expression is expressed as follows:

When C, use formula (13) to update the next generation; when B, use formula (16) to update the next generation. However, in this stage, whale algorithm is easy to fall into local optimization, resulting in relatively low accuracy. Therefore, this paper improves the position update formula by introducing inertia weight, which is expressed as follows: