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Abstract:
The paper is devoted to new computational techniques in structural dynamics where one tries to study, model, analyse and optimise very complex phenomena, for which more precise scientific tools of the past were incapable of giving low cost and complete solution. Soft computing methods differ from conventional (hard) computing in that, unlike hard computing, they are tolerant of imprecision, uncertainty, partial truth and approximation. The paper deals with an application of the bio-inspired methods, like the evolutionary algorithms (EA), the artificial immune systems (AIS) and the particle swarm optimisers (PSO) to optimisation problems. Structures considered in this work are analysed by the finite element method (FEM) and the boundary element method (BEM). The bio-inspired methods are applied to optimise shape, topology and material properties of 3D structures modelled by the FEM and to optimise location of stiffeners in 2D reinforced plates modelled by the coupled BEM/FEM. The structures are optimised using the criteria dependent on frequency, displacements or stresses. Numerical examples demonstrate that the methods based on the soft computation are effective for solving computer aided optimal design problems.

Keywords:
Soft computing, Evolutionary algorithm, Artificial immune system, Particle swarm optimiser, Optimisation, Finite element method, Boundary element method, Dynamics

Abstract:
In the paper an application of the particle swarm optimizer (PSO) and artificial immune system (AIS) to optimization problems is presented. Reinfored structures considered in this work are dynamically loaded and analyzed by the coupled boundary and finite element method (BEM/FEM). The metod is applied to optimize location of stiffeners in plates using criteria depended on displacements. The main advantage of the particle swarm optimizer, contrary to gradient methods of optimization, is the fact that it does not need any information about the gradient of fitness function. A comparison of the PSO, artificial immune system and evolutionary algorithm (EA) is also shown and it proves the efficiency of the former over other artificial intelligence methods of optimization. The coupled BEM/FEM, which is used to analyse structures, is very accu-rate in analysis and attractive in optimization tasks. It is because of problem dimensionality reduction in comparison with more frequently used domain methods, like for instance the FEM. Numerical examples demonstrate that the combination of the PSO with the BEM/FEM is an effective technique for solving computer aided optimal design problems, both with respect to accuracy and computational resources.

Keywords:
Particle swarm optimization, Immune optimization, Boundary element method, Finite element method, Dynamics