Introduction to Stochastic Search and Optimization
Introduction to Stochastic Search and Optimization
A heuristic particle swarm optimizer for optimization of pin connected structures
Computers and Structures
Particle swarm approach for structural design optimization
Computers and Structures
A hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
Crack detection in beam-like structures using genetic algorithms
Applied Soft Computing
Locating the critical failure surface in a slope stability analysis by genetic algorithm
Applied Soft Computing
Particle swarm optimization with adaptive population size and its application
Applied Soft Computing
Optimum design of structures by an improved genetic algorithm using neural networks
Advances in Engineering Software - Selected papers from civil-comp 2003 and AlCivil-comp 2003
Hi-index | 0.00 |
An efficient optimization procedure is introduced to find the optimal shapes of arch dams considering fluid-structure interaction subject to earthquake loading. The optimization is performed by a combination of simultaneous perturbation stochastic approximation (SPSA) and particle swarm optimization (PSO) algorithms. This serial integration of the two single methods is termed as SPSA-PSO. The operation of SPSA-PSO includes three phases. In the first phase, a preliminary optimization is accomplished using the SPSA. In the second phase, an optimal initial swarm is produced using the first phase results. In the last phase, the PSO is employed to find the optimum design using the optimal initial swarm. The numerical results demonstrate the high performance of the proposed strategy for optimal design of arch dams. The solutions obtained by the SPSA-PSO are compared with those of SPSA and PSO. It is revealed that the SPSA-PSO converges to a superior solution compared to the SPSA and PSO having a lower computation cost.