Research On Improvement And Application Of Seagull Optimization Algorithm

The Seagull Optimization Algorithm(SOA)is a new meta-heuristic algorithm proposed by simulating the migration and attack behavior of seagulls.It has the characteristics of simple structure,easy operation,and high efficiency.However,this algorithm has some shortcomings,such as being easy to trap into local optimum,slow convergence speed,and low calculation accuracy.Therefore,this paper improves some shortcomings of the seagull optimization algorithm,proposes three different versions of the seagull optimization algorithm,and applies them to solve complex optimization problems in real life,to further improve the search performance of the SOA algorithm and expand its application field.The main research contents of this thesis are as follows:(1)To improve the overall optimization ability of the algorithm,a whale hybrid seagull optimization algorithm(WSOA)is proposed by combining the shrinkage and encirclement mechanism of the whale optimization algorithm with the SOA algorithm.In addition,a flight strategy is introduced to avoid falling into local optimization of the SOA algorithm.The experimental results show that the WSOA algorithm has better performance than other algorithms in function optimization and engineering optimization problems.(2)To enhance the local search ability of the algorithm,inspired by the principle of symbiotic search algorithm(SOS),a mutual benefit and partial benefit symbiosis mechanism are introduced,and an enhanced seagull optimization algorithm(ESOA)is proposed.To evaluate the performance of the ESOA algorithm,it is applied to 12 different types of complex engineering design optimization problems.The experimental results show that the ESOA algorithm can provide optimal solutions to engineering optimization problems.(3)To solve the problem of time-consuming and high cost in the process of parallel machine scheduling with a traditional optimization algorithm,dynamic inertia weight and mutation strategies are introduced.An improved seagull optimization algorithm(ISOA)is proposed and applied to solve unrelated parallel machine scheduling problems.The results show that the ISOA algorithm can obtain the minimum completion time in solving unrelated parallel machine scheduling problems,and the search performance is better than other algorithms.