Tadeusz Burczyński

Optimization and defect identification using distributed evolutionary algorithms

Abstract The aim of the paper is to present the application of the distributed evolutionary algorithms to selected optimization and defect identification problems. The coupling of evolutionary algorithms with the finite element method and the boundary element method creates a computational intelligence technique that is very suitable in computer aided optimal design. Several numerical examples for shape, topology optimization and identification are presented for elastic, thermoelastic and elastoplastic structures.

Comparing binary and real-valued coding in hybrid immune algorithm for feature selection and classification of ECG signals

The paper presents a new algorithm for feature selection and classification. The algorithm is based on an immune metaphor, and combines both negative and clonal selection mechanisms characteristic for B- and T-lymphocytes. The main goal of the algorithm is to select the best subset of features for classification. Two level evolution is used in the proposed system for detectors creation and feature selection. Subpopulations of evolving detectors (T-lymphocytes) are able to discover subsets of features well suited for classification. The subpopulations cooperate during evolution by means of a novel suppression mechanism which is compared to the traditional suppression mechanism. The proposed suppression method proved to be superior to the traditional suppression in both recognition performance and its ability to select the proper number of subpopulations dynamically. Some results in the task of ECG signals classification are presented. The results for binary and real coded T-lymphocytes are compared and discussed.

Modeling and forecasting financial time series with ordered fuzzy candlesticks

Abstract The goal of the paper is to present an experimental evaluation of fuzzy time series models which are based on ordered fuzzy numbers to predict financial time series. Considering this approach the financial data is modeled using Ordered Fuzzy Numbers (OFNs) called further by Ordered Fuzzy Candlesticks (OFCs). The use of them allows modeling uncertainty associated with financial data and maintaining more information about price movement at assumed time interval than comparing to commonly used price charts (e.g. Japanese Candlestick chart). Thanks to well-defined arithmetic of OFN, one can construct models of fuzzy time series, such as an Ordered Fuzzy Autoregressive Process (OFAR), where all input values are OFC, while the coefficients and output values are arbitrary OFN; in the form of classical equations, without using rule-based systems. In an empirical study ordered fuzzy autoregressive models are applied to modeling and predict price movement of futures contracts on Warsaw Stock Exchange Top 20 Index.

The identification of cracks using boundary elements and evolutionary algorithms

This paper is devoted to the identification problems for structures which contain cracks. The problem of crack identification is formulated as the minimization of the difference between the measured and computed values of displacements or stresses at selected boundary nodes. The coupling of the dual boundary element method and evolutionary algorithms is proposed to solve the problem. The identification of single cracks of different shapes is presented. The multiple crack identification is also considered. The problem of the identification of unknown number of cracks is formulated by introducing a special kind of chromosome. The influence of random errors in experimentally measured displacements on a convergence of the evolutionary identification is examined. A hybrid evolutionary approach based on sensitivity information of the fitness function is tested. Several numerical examples are presented.

Sensitivity analysis for shape perturbation of cavity or internal crack using BIE and adjoint variable approach

This paper deals with the application of the adjoint variable approach to sensitivity analysis of objective functions used for defect detection from knowledge of supplementary boundary data, in connection with the use of BIE/BEM formulations for the relevant forward problem. The main objective is to establish expressions for crack shape sensitivity, based on the adjoint variable approach, that are suitable for BEM implementation. In order to do so, it is useful to consider first the case of a cavity defect, for which such boundary-only sensitivity expressions are obtained for general initial geometry and shape perturbations. The analysis made in the cavity defect case is then seen to break down in the limiting case of a crack. However, a closer analysis reveals that sensitivity formulas suitable for BEM implementation can still be established. First, particular sensitivity formulas are obtained for special shape transformations (translation, rotation or expansion of the crack) for either two- or three-dimensional geometries which, except for the case of crack expansion together with dynamical governing equations, are made only of surface integrals (three-dimensional geometries) or line integrals (two-dimensional geometries). Next, arbitrary shape transformations are accommodated by using an additive decomposition of the transformation velocity over a tubular neighbourhood of the crack front, which leads to sensitivity formulas. This leads to sensitivity formulas involving integrals on the crack, the tubular neighbourhood and its boundary. Finally, the limiting case of the latter results when the tubular neighbourhood shrinks around the crack front is shown to yield a sensitivity formula involving the stress intensity factors of both the forward and the adjoint solutions. Classical path-independent integrals are recovered as special cases. The main exposition is done in connection with the scalar transient wave equation. The results are then extended to the linear time-domain elastodynamics framework. Linear static governing equations are contained as obvious special cases. Numerical results for crack shape sensitivity computation are presented for two-dimensional time-domain elastodynamics.

Sequential and Distributed Evolutionary Computations in Structural Optimization

The aim of the paper is to present the application of the sequential and distributed evolutionary algorithms to selected structural optimization problems. The coupling of evolutionary algorithms with the finite element method and the boundary element method creates a computational intelligence technique that is very suitable in computer aided optimal design. Several numerical examples for shape, topology and material optimization are presented.

Optimization of Structures Using Distributed and Parallel Evolutionary Algorithms

This paper is devoted to applications of evolutionary algorithms into optimal design of nonlinear structures and identification of holes. The parallel and the distributed evolutionary algorithms are considered. The optimum criterion is to minimize the plastic strain areas and stress values or an identification functional. The fitness functions are computed using the finite element method or the coupled finite and boundary element method.

Immune identification of piezoelectric material constants using BEM

This article deals with an application of the artificial immune system (AIS) to the identification problem of piezoelectric structures analysed by the boundary element method (BEM). The AIS is applied to identify material properties of piezoelectrics. The AIS is a computational adaptive system inspired by the principles, processes and mechanisms of biological immune systems. The algorithms typically use the characteristics of immune systems, such as learning and memory to simulate and solve a problem in a computational manner. The main advantage of the AIS, contrary to gradient methods of optimization, is the fact that it does not need any information about the gradient of fitness function.

Topological evolutionary computing in the optimal design of 2D and 3D structures

An application of evolutionary algorithms and the finite-element method to the topology optimization of 2D structures (plane stress, bending plates, and shells) and 3D structures is described. The basis of the topological evolutionary optimization is the direct control of the density material distribution (or thickness for 2D structures) by the evolutionary algorithm. The structures are optimized for stress, mass, and compliance criteria. The numerical examples demonstrate that this method is an effective technique for solving problems in computer-aided optimal design. †This is an extended and enhanced version of work presented at the mini−symposium on Evolutionary Algorithms: Recent Applications in Engineering and Science organized by Dr William Annicchiarico at the 7th World Congress on Computational Mechanics, Los Angeles, July 2006.

Evolutionary methods in inverse problems of engineering mechanics

Publisher Summary This paper deals with applications of evolutionary algorithms to inverse problems of engineering mechanics. Evolutionary algorithms are considered as modified and generalized classical genetic algorithms in which populations of chromosomes are coded by floating point representation, and the new modified crossover and mutation operations are introduced. The evolutionary algorithm starts with a population of randomly generated chromosomes from a feasible solution domain. These chromosomes, which have the vector structure, evolve toward better solutions by applying genetic operators such as selection, mutation, and crossover. After applying genetic operators, the new population has a better fitness. The probability of crossover and mutation does not have to be constant as in classical genetic algorithms and it can change during the evolutionary process. An objective function (fitness function) with constraints plays the role of the environment to distinguish between good and bad chromosomes and to select the better solution.