Multi-objective Optimization Design Method Of Bridge Piers Based On Particle Swarm Optimization Algorithm

To optimize the anti-seismic design of reinforced concrete bridge pier structure, particle swarm optimization algorithm and response spectrum analysis were combined to construct the anti-seismic design optimization framework of regular circular single column bridge pier, with respect to the cross section features and reinforcement ratio as its design variables and the anti-seismic demand ability ratio as its objective function, for the purpose of converting the anti-seismic design to multiple target optimization. The results show that:the optimal design parameters satisfied multiple target demand was obtained fleetly in this method; the anti-seismic property of optimized bridge pier was improved apparently, which means this method is more intended for design intent, thus, there is great practical significance of design method presented in engineering application. Main works in this paper were listed as followed:1) Based on response spectrum method and multi-objective particle swarm optimization algorithm, computing framework of regular circular single column bridge pier was built with the cross section features and reinforcement ratio being selected as design variables. Besides, optimized design process and program implementation method were detailed as well.2) In the application of multi-objective particle swarm optimization algorithm in optimization design of bridge pier structure, the pareto solution set was concluded taking anti-bending axial force demand ability ratio (△ 1) and bending moment demand ability ratio (△ 2) under E1 seismic action, shear demand ability ratio (△ 3) and displacement ductility demand ability ratio (△ 4) of E2 seismic action as the objective functions.3) Through analyzing an example of regular bridge pier structure optimization design, though the materials consumption increased in this method, the anti-seismic property enhanced greatly, and the optimization results satified the requirements of bridge engineering design. Moreover, influences of population size, learning factor and blend function in the process of optimization were discussed.4) On the background of the example listed, with the application of genetic algorithm, comparisons between genetic algorithm and particle swarm optimization was made, the results indicate that, particle swarm optimization algorithm was preferable than genetic algorithm in solution set convergence and algorithm robustness as the demand of highway bridge seismic design conditions was satisfied. The optimization results show that, the ductility design framework of regular circular single bridge pier in this paper is feasible and possesses great practical significance in engineering application.