Truss Structure Optimization Based On Improved Wolf Pack Algorithm

Structural optimization design is a design scheme that can reasonably design the structure and make the evaluation indexes such as weight,stiffness and cost better under the restriction of satisfying the specification requirements and specific requirements.Optimization of the structural components can not only greatly reduce the weight and cost of the structure,but also help to improve the strength and stiffness of the structure and improve the structural performance.The truss structure have many advantages,such as high comprehensive utilization rate of materials,relatively light weight,strong bearing capacity,convenient construction,good assembly,good assembling and recycling,etc.It has been widely used in construction structures.Therefore,the truss structure optimization method has important significance to the structural optimization design.With the increasing complexity of structural forms,the calculation accuracy and convergence speed of the traditional optimization design methods for building structures can’t fully meet the needs of practical construction projects.In recent years,computational intelligence optimization algorithms have been gradually developed and applied to structural intelligence optimization,and good optimization results have been obtained.Wolf pack algorithm is a new kind of intelligent computing method with strong ability to search for optimal.However,in the traditional wolf pack algorithm,there are often some common problems,such as falling into local optimal and low precision.In order to find a more effective structural optimization method,this dissertation proposes an improved wolf pack algorithm based on adaptive step size and levy flight strategy,combining the improved wolf pack algorithm with truss structure optimization design,it is hoped to provide a new calculation method and design idea for truss designers.The improved method of the wolf pack optimization algorithm was to add a random disturbance factor into the initialization process of the wolves to expand the randomness of the search and improve global optimization performance;Then,the search strategy of levy flight random walk was adopted when the wolf scout executed the wandering behavior,which made the algorithm search more fully in the later stage and improved the search ability;Finally,the adaptive step size strategy was introduced in the course of the wolf running,and the adaptive adjustment of the algorithm was realized through the reasonable change of the adaptive step size,which not only improved the search accuracy but also shortened the time to find the optimal solution.In order to verify the reliability of the improved wolf pack algorithm,it was applied to solve the traveling salesman problem,and the simulation analysis showed that the improved algorithm had higher reliability.In the end,the improved wolf pack algorithm is combined with the optimization design of the truss structure,the cross-sectional area of the truss structure as basic optimization variables,and the overall quality of the structure is taken as the objective function of the truss optimization design.By constructing the basic mathematical model of the structure,using the improved wolf pack algorithm to optimize the solution of the model,and compared with other algorithms.The analysis results show that the improved wolf pack algorithm is more effective in dealing with the truss optimization problem and achieves the purpose of reducing the weight of the structure.This study provides a new solution for the structural optimization problem.