| Structural optimization can make the structure safe,beautiful and practical by reasonably arranging the node position or controlling the cross-sectional area of the bar,but also has economic benefits and promotes the sustainable development of society.In the past,people mainly used the mechanical criterion method and mathematical programming method to optimize the design of the structure.The scope of application is relatively small,and it is not suitable for practical engineering projects.In recent years,with the progress of society,computer technology has been rapidly developed,and swarm intelligence algorithms have been more and more widely used in structural optimization design.The slime mold algorithm is a meta-heuristic algorithm with the advantages of few parameters and strong optimization ability.However,in the later optimization process,most of the slime mold individuals will search for the space with high food concentration,losing the diversity of optimization,resulting in a significantly slower convergence rate in the later period.In this paper,a variety of strategies are introduced to improve the viscosity optimization algorithm,and the improved algorithm is applied to the classical truss examples and practical engineering problems for effectiveness analysis.The main research contents and conclusions are as follows :(1)The reverse elite strategy is introduced in the initialization process,and the individuals with better fitness values are selected as the initial population individuals in the current population and the reverse population to increase their diversity.The global exploration and local development ability of the adaptive adjustable feedback factor coordination algorithm is introduced at the update position of the slime mold individual.Finally,through the mutation operation of the differential algorithm,the algorithm jumps out of the local optimum and avoids the premature convergence of the algorithm to some extent.(2)The improved myxobacteria optimization algorithm is compared with the basic myxobacteria optimization algorithm,the wild horse optimization algorithm,the vulture search optimization algorithm,the artificial power plant optimization algorithm,and the particle swarm optimization algorithm using 8 different types of standard test functions in the same experimental environment.The validity analysis is carried out in different dimensions,and the improved algorithm is applied to the classical traveling salesman problem,which has achieved good results.Finally,the classical optimization problems of 10-bar,25-bar,72-bar and 200-bar truss structures are selected and solved by the improved algorithm.It can be seen that the algorithm in this paper is superior to other algorithms in the optimization design of truss structure.(3)The The main truss beam structure of ZHJ-1 and ZHJ-4 in the truss roof of a city gymnasium is optimized.The particle swarm optimization algorithm,the slime mold optimization algorithm and the improved slime mold optimization algorithm are compared.The results show that the optimized mass of the main truss beam of ZHJ-1section is 10097.51 kg,and the optimized mass of the main truss beam of ZHJ-4 section is 18981.82 kg.Compared with the particle swarm optimization algorithm,the structural quality is optimized by 1.96 % and 1.13 % respectively.Compared with the myxomycete optimization algorithm,the structural quality was optimized by 3.08 %and 7.59 %,respectively.Compared with the improved myxomycetes optimization algorithm,the structure quality is optimized by 9.05 % and 9.75 % respectively.The improved sticky bacteria optimization algorithm has obvious advantages in solving practical engineering problems such as trusses,and provides a new idea for truss examples and similar practical engineering problems. |
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