A Heterogeneous Strategy Genetic Algorithm and its Application in Dynamic Optimization of Structure

Le Wei Yan; Yang Yang Chen

doi:10.4028/www.scientific.net/AMM.204-208.4827

Paper Titles

Positive Radial Solutions for Elliptic Systems with Nonlocal Conditions
p.4800

Design and Implementation of the Simulation Model of a Certain Communication Gateway
p.4809

Digital Image Measurement Technology for High-Rise Structure Torsion Deformation Measuring
p.4813

Research on Numerical Integration Algorithm for MDOF Pseudo-Dynamic Test
p.4820

A Heterogeneous Strategy Genetic Algorithm and its Application in Dynamic Optimization of Structure
p.4827

Rules of CST Blunt Edge Roundness and the Influence on Collision Characteristics
p.4831

Oscillation Criterion of Third-Order Nonlinear Neutral Damped Functional Differential Equations
p.4835

Deterministic Method of Floor Rock Permeability Tensor of Mining over Confined Water and Application in Numerical Simulation
p.4840

Structure Optimal Design for Portable Exoskeleton Using Improved Particle Swarm Optimization
p.4845

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 204-208A Heterogeneous Strategy Genetic Algorithm and its...

A Heterogeneous Strategy Genetic Algorithm and its Application in Dynamic Optimization of Structure

Abstract:

Heterogeneous strategy is used to improve genetic algorithm. It can increase the population diversity and avoid premature while the convergence efficiency is ensured. Furthermore, an expression to estimate the extent of inbreeding and two methods for selecting heterogeneity were given, and, an improved generalized genetic algorithm was presented in this paper. This algorithm is used for multi-parameter dynamic optimization of the structure which is under random loads and has stress constrains. Numerical examples demonstrated that heterogeneous strategy can improve the probability of convergence to global optimal solution and the improved generalized genetic.

You might also be interested in these eBooks

Progress in Industrial and Civil Engineering

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 204-208)

Pages:

4827-4830

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.204-208.4827

Citation:

Cite this paper

Online since:

October 2012

Authors:

Le Wei Yan*, Yang Yang Chen

Keywords:

Dynamic optimization, Genetic Algorithm (GA), Heterogeneous Strategy, Stress Constrain

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Christodoulou K. Structural model updating and prediction variability using Pareto optimal models [J]. Computer methods in applied mechanics and engineering. 198: 138-149 (2008).

DOI: 10.1016/j.cma.2008.04.010

Google Scholar

[2] Qiu Z P, Hu J X, Yang H L, Lu Q S. Exact bounds for the sensitivity analysis of structures with uncertain-but-bounded parameters Applied Mathematical Modelling, 2008, 32(6): 1143-1157.

DOI: 10.1016/j.apm.2007.03.004

Google Scholar

[3] Hu X B, Di Paolo E, An efficient genetic algorithm with uniform crossover for air traffic control. Computer and Operations Research, 2009, 36(1): 245-259.

DOI: 10.1016/j.cor.2007.09.005

Google Scholar

[4] Mohamed J A H, Sivakumar R. A survey: hybrid evolutionary algorithms for cluster analysis. Artificial Intelligence Review, 2011: 1-26.

Google Scholar

[5] Misevicius A. Genetic algorithm hybridized with ruin and recreate procedure: Application to the quadratic assignment problem. Knowledge-Based Systems, 2003, 16(5-6): 261-268.

DOI: 10.1016/s0950-7051(03)00027-3

Google Scholar

[6] Gerald W., Remegio C.J., Stephen M. G., Rolf F., Shawna G., Jeffrey J. S., George W. M., and Gary M. B. A hybrid genetic algorithm for multi－objective problems with activity analysis-based local search. European Journal of Operational Research. 193, 195-203 (2009).

Google Scholar