A competitive comparison of different types of evolutionary algorithms

Abstract

This paper presents comparison of several stochastic optimization algorithms developed by authors in their previous works for the solution of some problems arising in Civil Engineering. The introduced optimization methods are: the integer augmented simulated annealing (IASA), the real-coded augmented simulated annealing (RASA), the differential evolution (DE) in its original fashion developed by R. Storn and K. Price and simplified real-coded differential genetic algorithm (SADE). Each of these methods was developed for some specific optimization problem; namely the Chebychev trial polynomial problem, the so called type 0 function and two engineering problems - the reinforced concrete beam layout and the periodic unit cell problem respectively. Detailed and extensive numerical tests were performed to examine the stability and efficiency of proposed algorithms. The results of our experiments suggest that the performance and robustness of RASA, IASA and SADE methods are comparable, while the DE algorithm performs slightly worse. This fact together with a small number of internal parameters promotes the SADE method as the most robust for practical use.Comment: 25 pages, 8 figures, 5 table

Optimum Structural Design Using Bio-Inspired Search Methods: A Survey and Applications

“…Hrstka et al [77] address a problem of optimal configuration of a reinforced concrete beam, and also the configuration of a unit periodic cell of composite materials, by comparing several recent evolutionary algorithms.…”

Differential Evolution Algorithm for Dynamic Structural Identification

“…On the contrary, direct search methods (such as DE) are very efficient when the number of parameters to be identified increases and, consequently, sensitivity of cost function to parameter variation is typically very small (see, for instance, Hrstka et al, 2003). In fact, these methods do not require computation of gradient and Hessian matrix.…”

“…In this case, classical algorithms often fail due to ill conditioning of optimization problems [Vanderplaats, 1984]. On the contrary, direct search algorithms, such as DE, typically converge also when the number of parameters is very high [Hrstka et al, 2003]. …”

Homogenization of balanced plain weave composites with imperfect microstructure: Part I––Theoretical formulation

“…The detailed description of this algorithm, list of used operators as well as some tests of its performance can be found in Matou s et al (2000) and Hrstka et al (2003). See also Zeman (2003) for values of individual parameters of this method for the current optimization problems.…”