Research On Improvement And Application Of Salp Swarm Algorithm

As the scale of various optimization problems in practical production becomes more and more complex,it is more and more difficult to solve the optimization problems.Scholars at home and abroad begin to pay attention to the use of heuristic algorithm to solve the optimization problem.Evolutionary algorithm is a kind of metaheuristic algorithm based on swarm intelligence.Because of its universal applicability and effectiveness,evolutionary algorithm has gradually become a global optimization algorithm with a very broad application prospect.Salp swarm algorithm is a new evolutionary algorithm proposed by Mirjalili et al.2017.With the characteristics of easy implementation,and less control parameters,it is widely used in the research of smart grid fault self-healing control,enhanced power inspection image,photovoltaic system and other fields.However,this algorithm also has some defects.For example,salp swarm algorithm is easy to fall into local optimum and cannot be directly used to solve combinatorial optimization problems in discrete domain.This paper proposes a discrete salp swarm algorithm based on transfer function discretization and adding the random crossover mechanism of individual followers in its evolution process,which is denoted as DSSA.On this basis,an individual mutation mechanism is added to improve the algorithm,denoted as MDSSA.The discounted 0-1 knapsack problem and multidimensional knapsack problem are used to test the optimization ability and robustness of the two algorithms.Finally,MDSSA is used to solve the load management problem of multi-electric aircraft,and a new method to solve the problem is presented.The research content of this paper is as follows:1.Salp swarn algorithm for discretization,and followers in the process of its evolution to join the individual randomized crossover mechanism,this paper proposes a new discretization salp swarm algorithm which denoted as DSSA,and applied it in solving discounted 0-1 knapsack problem,choose the most suitable solution and the best control parameters of transfer function,finally comparing with many kinds of algorithms,The performance of the algorithm is verified.2.On the basis of DSSA,in order to increase the population diversity and search ability of the algorithm,a novel individual mutation mechanism is added to propose another novel discrete salp swarm algorithm MDSSA,which is applied to solve the multidimensional knapsack problem,and its performance is verified by comparing with other algorithms.3.Apply MDSSA to solve the load management problem of multi-electric aircraft,and verify the effectiveness and excellence of using MDSSA to solve the load management problem of multi-electric aircraft by comparing with various algorithms through experiments.