Research And Application In Engineering Optimization Problems Of Improved Salp Swarm Algorithm

Salp Swarm Algorithm(SSA)is a meta-heuristic Algorithm based on Salp's predation behavior,which has been certificated that can solve many optimization problems in nature.The algorithm has the characteristics of uncomplicated structure,little control parameters and small amount of calculation.When it was proposed,it has been studied by many people widely.SSA has some shortcomings,low search precision,the speed of convergence is limited,and the search individual is also easy to get stuck in the local area,which limits the effect of the algorithm on development,and its ability to explore globally is also affected.Therefore,the SSA algorithm still has some problems to be studied,and there is still room for progress in improving the efficiency of the algorithm and improving the optimization performance of the algorithm in practical problems.In this paper,the parameters and characteristics of the salp swarm algorithm were studied,we improve the salp swarm algorithm in many aspects,and the application of the improved algorithm in problems of engineering optimization explored further.The main work of this paper is as follows:First,we propose the improved salp swarm algorithm based on simulated annealing algorithm(SASSA).Among them,considering the lack of population diversity in the early population of the basic salp swarm algorithm,chaos mapping was introduced to initialize the population,and for the problem of population division of irrational algorithms,introduced adaptive population division and combined with simulated annealing so that we will investigate further at a later stage of the iteration.The capabilities of the improved salp swarm algorithm are evaluated by benchmark functions,and to objectively evaluate the performance of the algorithm,four popular metaheuristic algorithms is introduced and the results are compared with the improved algorithm.Experimental results prove the effectiveness of the SASSA for benchmark function problems,while also perform well at accuracy,speed of convergence and robustness.Second,the improved salp swarm algorithm is applied to the engineering optimization problem.Three classic engineering-optimized design problems are selected for simulation,and the improved algorithms is compared with six different algorithms.Experiments shows that the algorithm proposed in this paper perform also well at stability and accuracy.Convergence mode has been greatly improved.Compared to other heuristic algorithms,the SASSA algorithm can obtain more accurate results.