Study On The Heuristic Differential Evolution Method For The Payload Configuration And Packing Of A Multi-module Satellite

Layout problems with performance constraints derive from many applied domain,such as payload configuration and packing of multi-module satellite,billet cutting in steel enterprises,pipeline layout,industrial plant and facility layout design,which are NP-hard problems.Based on the satellite module loading problem as the research background,this paper mainly focuses on how to place regular objects on the four bearing plates in three-dimensional space,and under the given constraints,the moment of inertia of the entire loading scheme should be as small as possible,as should the envelope radius.At present,there are mainly evolutionary algorithms with random initial points and hybrid algorithms for this problem.The former has a large search space and time-consuming interference calculations that limit the performance of the algorithm.The latter is to construct feasible scheme by heuristic method and to optimize the packing order by swarm intelligence.In this problem,it is required to coordinated optimization of multi-module configuration and packing of payloads,otherwise it is difficult to achieve a balance optimization between conflicting indicators.Inspired by the no-free lunch theorem and existing approaches,this paper researches on payload configuration and packing of multi-module satellite and multi-module payload collaborative optimization.It mainly includes the combination of differential evolution algorithm and heuristic feasible scheme construction to optimize the rotational inertia and container radius of the multi-module satellite,and the particle swarm on the basis of beetle antennae search(BAS)to optimize the inertia angle and centroid eccentricity of the multi-module satellite.The innovation points mainly include the following two aspects:1.A partial order key heuristic difference algorithm has been presented to solve the moment of inertia and envelope radius of multi-module satellite.Based on the existing knowledge,the acquired knowledge is used to construct the initial population;the partial order key heuristic differential optimization mechanism is used to realize the co-optimization of payload configuration and single-module packing problem;a new fitness function is constructed to ensure the balance of envelope radius and rotational inertia is optimized.The experimental data shows that:compared with the proposed algorithm,the rotational inertia and container radius of multi-module satellite calculated by the algorithm are both smaller.2.A particle swarm optimization algorithm based on beetle antennae search(BAS)is proposed to optimize the inertia angle and centroid offset of multi-module satellites.Calculate the fitness function through the two mustards of the beetle.In the process of particle movement,use the beetle antennae search strategy to predict the left and right directions of the next step,so that the particles move to a better position in the next step,and the solution is better Layout scheme.The particle swarm optimization on the basis of the beetle whisker algorithm minimizes the resultant force of the four common forces,and reduces the satellite’s centroid offset and inertia angle.The empirical results show that the overall scheme calculated by the algorithm in this paper has a smaller inertia angle and center of mass offset.This paper mainly studies the international commercial communication satellite.To improve the solving accuracy of packing problem of the multi-module satellite,this paper deals with the payload configuration and constrained packing of multi-module satellites,and solves the payload and packing scheme based on the regional positioning strategy.It is hoped that the method and strategy proposed in this paper can provide enlightenment for more complex layout optimization problems.