Wyniki wyszukiwania - BazTech

1

On Updating Finite Element Models of Real Structures Using Genetic Algorithm

Touat N., Pyrz M., Rechak S.

Machine Dynamics Problems

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2008

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Vol. 32, No. 2

74-87

EN

An efficient method of updating numerical models for dynamics problems is presented. The objective is to minimize the difference between measured and simulated vibration data. The corresponding optimization problem is formulated in the modal domain and solved using the genetic algorithm (GA) stochastic algorithm. Original modifications of a standard GA are proposed to improve the updating process efficacy. New versions of GA exploit the speeding up procedures developed in the novel accelerated random search (ARS) algorithm. A finite element model of a lumped mass structure is analyzed to validate the approach. A real beam-like structure model is updated, making use of experimental modal data. The enhanced GA enables us to obtain results well correlated with experiments.

2

Simulation-based optimization; methods and practical application

Niewiadomska-Szynkiewicz E.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2006

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z. 156

291-300

EN

The paper is concerned with computational research for complex systems. The simulation-based optimization approach, which is widely used in applied science and engineering, is formulated and discussed. The numerical techniques that optimize performance of system by using simulation to evaluate the objective value are reviewed. The focus is on random search and metaheuristics. The practical example - application of simulation optimization to calculate the optimal decisions for controlling the river-basin reservoir system during flood period is presented and discussed.

3

Parallel and distributed Controlled Random Search algorithms; case study results

Marks M., Niewiadomska-Szynkiewicz E.

Prace Naukowe Politechniki Warszawskiej. Elektronika

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2006

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z. 156

263-272

EN

CRS (Controlled Random Search) algorithms for global optimization are considered. The main objective is to present the advantages of developing the parallel and distributed random search algorithms to search for the global solution. A practical example, application of parallel CRS2, CRS4, CRS6, CRSI algorithms and distributed CRS2 algorithm to calculate the optimal prices of products that are sold in the market, are presented. In the final part of the paper the results of numerical experiments performed on the historical data are described and discussed.

4

Hybrid search for optimum in a small implicitly defined region

Zilinskas A.

Control and Cybernetics

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2004

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Vol. 33, no 4

599-609

EN

We consider optimization problems with a small implicitly denned feasible region, and with an objective function corrupted by irregularities, e.g. small noise added to the function values. Known mathematical programming methods with high convergence rate can not, lie applied to such problems. A hybrid technique is developed combining random search for the feasible region of a considered problem, and evolutionary search for the minimum over the found region. The solution results of two test problems and of a difficult real world problem are presented.