Hybrid Particle Swarm Optimization Method Study Of Bridge Crane Box Girder

Bridge crane has been basically formed a pattern of universal and serialization as a largelifting handling equipment in the national economy development and construction. In theNational Science and Technology Support Program in2015, the research and application ofbridge Crane lightweight design key technology was listed to be the primary task in themanufacturing field. So it is important to explore a practical and effective optimization designmethod for lightweight design of the bridge crane key components.Bridge crane main girder optimization design is a kind of nonlinear discrete variablescomplex optimization problem which is with multi-dimensional, multi-constrained.Thetraditional optimization methods to solve this problem exist various limitate.So this paperpresents a hybrid particle swarm optimization algorithm for bridge crane girder optimizationdesign. The main contents are as followed:(1) Given the process of the crane main girder optimization design based on the analysisof crane structure optimization features.(2) Setting the sectional area of bridge crane box girder as objective function, Setting thefive dimensions of girder sectional parameters as design variables.Setting the mechanicsperformance, manufacturing process, boundary dimensions of crane girder as constraints, theoptimization model of bridge crane girder is established.(3) Analysis the advantages and disadvantages of Particle Swarm Optimization andSimulated Annealing, the thesis fused the Simulated Annealing Algorithm’s Metropoliscriterion to the Linear Inertia Weight Particle Swarm Optimization Algorithm (LWPSO), sowe get the SA-LWPSO Hybrid Optimization Method. This paper presents the method whichcombined the penalty function with the above-mentioned hybrid optimization method asbridge crane girder belongs to constrained optimization problem. (4) Simulation experiment is carried out by using standard test functions and crane girderoptimization test case, and to make a comparison with the published literature, this hybridalgorithm has advantages on optimization results and algorithms performance.(5) Taking a32t double girder bridge crane box girder as an engineering example, usingthe basic PSO algorithm and hybrid optimization algorithm to complete bridge crane boxgirder Optimal design based on Matlab programming language. The optimization results showthat the basic PSO algorithm reduces13.5%than girder sectional area before optimization inengineering examples, hybrid particle swarm optimization algorithm reduces20.3%. Finally,Verify the feasibility of the optimization results by analyzing the before and after optimizationmodels through ANSYS finite element simulation.