A numerical method combining finite element analysis and a hybrid genetic algorithm is proposed to inversely determine the elastic constants from the vibration testing data. As verified from composite material specimens, the repeatability and accuracy of the proposed inverse determination method are confirmed, and it also proves that the concept of effective elastic constants is workable. Moreover, three different sets of assumptions to reduce the five independent elastic constants to four do not make clear difference on the obtained results by the proposed method. In addition, to obtain robust values of the five elastic constants for a transversely isotropic material, it is recommended to use the out-of-plane Poisson's ratio instead of the out-of-plane shear modulus as the fifth one.

Abstract. In this paper, a technology enabling the optimization of the topology of truss or frame structures with genetic algorithms is presented. It has been shown that due to a huge number of possible variants the global solution of similar problems with exhaustive search algorithms is feasible only for systems possessing small numbers of d.o.f. s (usually until 10 nodes). These problems can be solved in a reasonable time by genetic algorithms. The modified genetic algorithm for optimization of topology of truss systems is suggested, where the repair of the genotype, instead of some constraint is used. The solution of numerical examples with original software illustrates the efficiency of proposed technology; the global solutions are obtained in all cases.

Abstract. Present paper describes the facilities of composite material properties identification technique using specimen vibration tests, genetic algorithms, finite elements analysis and specimen shape optimization. In identification process the elastic constants in a numerical model is updated so that the output from the numerical code fits the results from vibration testing. Main problem analysed in this paper is that Poisson's ratio is the worst determined elastic characteristic due to its low influence on specimen eigenfrequencies. It is shown that it is possible to increase its influence by choosing specific test specimen characteristics (side aspect ratio, orthotropy angle, etc.) via optimization routine. In this paper are presented test results of some experiments wherein glass-epoxy and carbonepoxy material properties were identified.

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The mathematical models and solution algorithms for optimization of grillage-type foundations arc presented. Optimization of grillage is based on optimization of separate beams comprising grillage. Minimising of maximum in absolute value vertical reactive force, bending moment, and reaction-bending moment together is sought in a separate beam. All these problems are non-linear, therefore are solved iteratively changing in each iteration the structure shape to a better neighbouring shape. Solution of this requires three steps: finite element analysis, analytical sensitivity analysis, and optimal re-design via linear mathematical programming. The main problem related to the proposed technique is to guarantee the global minimum solution. Engineering algorithm is suggested for avoidance of local minimum solutions: optimization procedure starts from quasi-optimal initial pile placement scheme, which is designed by a special expert system.

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In this paper, a new simplified version of the Bayesian Approach to coordinate global optimization (BAcoor) is compared with the well-known algorithms. BAcoor is a method of multi-dimensional optimization by applying a sequence of one-dimensional global optimizers starting from the best points obtained by previous one-dimensional optimization. The globality of one-dimension search is controlled by the only parameter. The new element is that observation points are defined by explicit formulas. In other similar methods this is performed by some numerical techniques that minimize the risk functions. The efficiency of suggested method is investigated and compared with other methods by solving a real-life civil engineering global optimization problem of pile placement schemes in grillage-type foundations. This problem is a good benchmark, because the minimal value of the objective function is known so the optimization error can be defined exactly.