Computational Technology Resources - CCP

Keywords: sensitivity analysis, discrete truss design, ant colony optimization, genetic algorithm, local search.

Summary

We present in this study a new hybrid meta-heuristic method (ANGEL) for solving discrete size optimization of shallow space structures with stability constraints [1].

ANGEL combines an ant colony optimization (ACO), a genetic algorithm (GA) and a local search (LS) strategy [2]. The applied basic strategies as elements of the proposed method ANGEL are discussed in this paper. For the first time, the ACO searches the solution space and generates structure designs to provide the initial population for the GA. After that, the GA is executed and the pheromone set in ACO is updated when the GA obtains a better solution. When the GA terminates, the ACO searches again by using the new pheromone set. The ACO and GA search alternately and cooperatively in the solution space. This study also proposes an efficient local search procedure, which is applied to yield a better solution when ACO or GA obtains a solution.

The geometrically and materially nonlinear space structure is formulated as a large displacement structural model. The method of elastic-plastic collapse analysis is based on a path-following method [3]. The applied method is a combination of the perturbation technique of the stability theory and the non-linear modification of the classical linear homotopy method. With the help of the higher-order predictor-corrector terms, the method is able to follow the load- deflection path even in case of elastic-plastic material law.

References

1: A. Csébfalvi, "A simulated annealing algorithm for discrete minimal weight design of shallow space trusses with stability constraints", WCCM-V Fifth World Congress on Computational Mechanics, July 7-12, 2002, Vienna, Austria, eds. H. A. Mang, F. G. Rammerstorfer, J. Eberhardsteiner, On-line publication (ISBN 3 9501554-0-6) Paper-ID: 81234, Session: RS 207.4, 2002.
2: A. Csébfalvi, "Probabilistic Diversification and Intensification in Local Search for Optimal Design of Shallow Space Trusses", Proc. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2004) P. Neittaanmäki, T. Rossi, K. Majava, and O. Pironneau (eds.) I. Lasiecka (assoc. ed.), Vol.I, p.355 +CD, 2004.
3: A. Csébfalvi, "A non-linear path-following method for computing the equilibrium curve of structures", Annals of Operation Research, 81: 15-23, 1998. doi:10.1023/A:1018944804979

purchase the full-text of this paper (price £20)

go to the previous paper
go to the next paper
return to the table of contents
return to the book description
purchase this book (price £75 +P&P)

	Computational & Technology Resources an online resource for computational, engineering & technology publications
	not logged in - login
Front Page Browse CCP CSETS CTR IJRT Other Authors Search Purchase Guide FAQ Contact us	Civil-Comp Proceedings ISSN 1759-3433 CCP: 85 PROCEEDINGS OF THE FIFTEENTH UK CONFERENCE OF THE ASSOCIATION OF COMPUTATIONAL MECHANICS IN ENGINEERING Edited by: B.H.V. Topping Paper 59 Optimum Design and Sensitivity Analysis of Shallow Space Structures using an Improved Meta-Heuristic Method A. Csébfalvi and G. Csébfalvi Pollack Mihaly Faculty of Engineering, University of Pécs, Hungary doi:10.4203/ccp.85.59 purchase the full-text of this paper Full Bibliographic Reference for this paper , "Optimum Design and Sensitivity Analysis of Shallow Space Structures using an Improved Meta-Heuristic Method", in B.H.V. Topping, (Editor), "Proceedings of the Fifteenth UK Conference of the Association of Computational Mechanics in Engineering", Civil-Comp Press, Stirlingshire, UK, Paper 59, 2007. doi:10.4203/ccp.85.59 Keywords: sensitivity analysis, discrete truss design, ant colony optimization, genetic algorithm, local search. Summary We present in this study a new hybrid meta-heuristic method (ANGEL) for solving discrete size optimization of shallow space structures with stability constraints [1]. ANGEL combines an ant colony optimization (ACO), a genetic algorithm (GA) and a local search (LS) strategy [2]. The applied basic strategies as elements of the proposed method ANGEL are discussed in this paper. For the first time, the ACO searches the solution space and generates structure designs to provide the initial population for the GA. After that, the GA is executed and the pheromone set in ACO is updated when the GA obtains a better solution. When the GA terminates, the ACO searches again by using the new pheromone set. The ACO and GA search alternately and cooperatively in the solution space. This study also proposes an efficient local search procedure, which is applied to yield a better solution when ACO or GA obtains a solution. The geometrically and materially nonlinear space structure is formulated as a large displacement structural model. The method of elastic-plastic collapse analysis is based on a path-following method [3]. The applied method is a combination of the perturbation technique of the stability theory and the non-linear modification of the classical linear homotopy method. With the help of the higher-order predictor-corrector terms, the method is able to follow the load- deflection path even in case of elastic-plastic material law. References 1 A. Csébfalvi, "A simulated annealing algorithm for discrete minimal weight design of shallow space trusses with stability constraints", WCCM-V Fifth World Congress on Computational Mechanics, July 7-12, 2002, Vienna, Austria, eds. H. A. Mang, F. G. Rammerstorfer, J. Eberhardsteiner, On-line publication (ISBN 3 9501554-0-6) Paper-ID: 81234, Session: RS 207.4, 2002. 2 A. Csébfalvi, "Probabilistic Diversification and Intensification in Local Search for Optimal Design of Shallow Space Trusses", Proc. European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS 2004) P. Neittaanmäki, T. Rossi, K. Majava, and O. Pironneau (eds.) I. Lasiecka (assoc. ed.), Vol.I, p.355 +CD, 2004. 3 A. Csébfalvi, "A non-linear path-following method for computing the equilibrium curve of structures", Annals of Operation Research, 81: 15-23, 1998. doi:10.1023/A:1018944804979 purchase the full-text of this paper (price £20) go to the previous paper go to the next paper return to the table of contents return to the book description purchase this book (price £75 +P&P)
Back to top	©Civil-Comp Limited 2023 - terms & conditions