Abstract：Seagulls algorithm(SOA) insufficient in solving optimization problem and algorithm performance depends on the selection of parameters such as faults,presents A Seagull optimization algorithm based on Inertia weight(Inertia Seagull optimization algorithm,I-SOA),using nonlinear decreasing Inertia weight calculation of additional variable A value to adjust the position of the gulls,through A levy flight and random index value increase the randomness of seagulls enhancement algorithm search optimization ability of global,avoid optimization search algorithm trapped in local optimal value; Twelve benchmark functions were used to test I-SOA against standard PSO,SOA and GA algorithms.Experimental results show that the proposed I-SOA optimization algorithm has fast convergence speed,high solution accuracy and global convergence ability.
2022, Vol. 43 
