Advanced solution methods in structural optimization based on evolution strategies (EN)

Cai, J (EN)

Thierauf, G (EN)

Papadrakakis, M (EN)

Lagaros, ND (EN)

The objective of this paper is to investigate the efficiency of hybrid solution methods when incorporated into large-scale optimization problems solved by evolution strategies (ESs) and to demonstrate their influence on the overall performance of these optimization algorithms. ESs imitate biological evolution and combine the concept of artificial survival of the fittest with evolutionary operators to form a robust search mechanism. In this paper modified multi-membered evolution strategies with discrete variables are adopted. Two solution methods are implemented based on the preconditioned conjugate gradient (PCG) algorithm. The first method is a PCG algorithm with a preconditioner resulted from a complete Cholesky factorization, and the second is a PCG algorithm in which a truncated Neumann series expansion is used as a preconditioner. The numerical tests presented demonstrate the computational advantages of the proposed methods, which become more pronounced in large-scale optimization problems and in a parallel computing environment. (EN)

journalArticle (EN)

Evolution-based systems (EN)

Structural design (EN)

Parameter estimation (EN)

hybrid techniques (EN)

Matrix algebra (EN)

structural optimization (EN)

Strategic planning (EN)

Mathematical techniques (EN)

Optimization (EN)

Genetic algorithms (EN)

Mathematics, Interdisciplinary Applications (EN)

Finite element method (EN)

Structural optimization (EN)

Simulated annealing (EN)

Calculations (EN)

Iterative methods (EN)

evolution strategies (EN)

Selection process (EN)

Computer Science, Interdisciplinary Applications (EN)

Computational methods (EN)

Engineering, Multidisciplinary (EN)

Evolution strategies (EN)

Natural processes (EN)

Hybrid techniques (EN)

Parallel processing systems (EN)

Mathematical operators (EN)

Algorithms (EN)

Neural networks (EN)

Mechanics (EN)

Problem solving (EN)

Performance (EN)

National Technical University of Athens

Digital Library of National Technical University of Athens | Dspace@NTUA

Κεντρική Βιβλιοθήκη Ε.Μ.Π.

Ιδρυματικό Αποθετήριο

Δημοσιεύσεις μελών Δ.Ε.Π. σε περιοδικά

Engineering Computations (Swansea, Wales) (EN)

English

1998 (EN)

http://hdl.handle.net/123456789/12562

0264-4401 (EN)

1 (EN)

12 (EN)

34 (EN)

10.1108/02644409810200668 (EN)

15 (EN)

ISI:000072522700002 (EN)

MCB UNIV PRESS LTD (EN)