Modified particle swarm optimization for optimum design of spread footing and retaining wall.

*(English)*Zbl 1400.74091Summary: This paper deals with the economically optimized design and sensitivity of two of the most widely used systems in geotechnical engineering: spread footing and retaining wall. Several recent advanced optimization methods have been developed, but very few of these methods have been applied to geotechnical problems. The current research develops a modified particle swarm optimization (MPSO) approach to obtain the optimum design of spread footing and retaining wall. The algorithm handles the problem-specific constraints using a penalty function approach. The optimization procedure controls all geotechnical and structural design constraints while reducing the overall cost of the structures. To verify the effectiveness and robustness of the proposed algorithm, three case studies of spread footing and retaining wall are illustrated. Comparison of the results of the present method, standard PSO, and other selected methods employed in previous studies shows the reliability and accuracy of the algorithm. Moreover, the parametric performance is investigated in order to examine the effect of relevant variables on the optimum design of the footing and the retaining structure utilizing the proposed method.

##### MSC:

74P10 | Optimization of other properties in solid mechanics |

90C15 | Stochastic programming |

90C59 | Approximation methods and heuristics in mathematical programming |

PDF
BibTeX
XML
Cite

\textit{M. Khajehzadeh} et al., J. Zhejiang Univ., Sci. A 12, No. 6, 415--427 (2011; Zbl 1400.74091)

Full Text:
DOI

##### References:

[1] | ACI 318-05, 2005. Building Code Requirements for Structural Concrete and Commentary. American Concrete Institute, Farmington Hills, MI, USA. |

[2] | Ahmadi-Nedushan, B.; Varaee, H., Optimal design of reinforced concrete retaining walls using a swarm intelligence technique, 26, (2009), Stirlingshire, UK |

[3] | Basudhar, P. K.; Vashistha, A.; Deb, K.; Dey, A., Cost optimization of reinforced Earth walls, Geotechnical and Geological Engineering, 26, 1-12, (2008) |

[4] | Bowles, J., 1982. Foundation Analysis and Design. McGraw-Hill, New York, USA. |

[5] | Budhu, M., 2006. Soil Mechanics and Foundations. John Wiley & Sons, New York, USA. |

[6] | Cheng, Y. M.; Li, L.; Chi, S. C., Performance studies on six heuristic global optimization methods in the location of critical slip surface, Computers and Geotechnics, 34, 462-484, (2007) |

[7] | He, Q. Y.; Han, C. J., An improved particle swarm optimization algorithm with disturbance term, Computational Intelligence and Bioinformatics, 4115, 100-108, (2006) |

[8] | He, S.; Wu, Q. H.; Wen, J. Y.; Saunders, J. R.; Paton, R. C., A particle swarm optimizer with passive congregation, Biosystems, 78, 135-147, (2004) |

[9] | Kennedy, J.; Eberhart, R., Particle swarm optimization, 1942-1948, (1995), Piscataway |

[10] | Kvam, P.H., Vidakovic, B., 2007. Nonparametric Statistics with Applications to Science and Engineering. John Wiley & Sons, New York, USA. [doi:10.1002/9780470 168707] · Zbl 1183.62207 |

[11] | Lee, K. S.; Geem, Z., A new structural optimization method based on the harmony search algorithm, Computers & Structures, 82, 781-798, (2004) |

[12] | Mendes, R.; Kennedy, J.; Neves, J., The fully informed particle swarm: simpler, maybe better, IEEE Transactions on Evolutionary Computation, 8, 204-210, (2004) |

[13] | Parsopoulos, K.E., Vrahatis, M.N., 2002. Particle Swarm Optimization Method for Constrained Optimization Problems. Proceedings of the Euro-International Symposium on Computational Intelligence, Košice, Slovakia. · Zbl 1018.68063 |

[14] | Paya-Zaforteza, I.; Yepes, V.; Hospitaler, A.; González-Vidosa, F., CO_{2}-optimization of reinforced concrete frames by simulated annealing, Engineering Structures, 31, 1501-1508, (2009) · Zbl 1337.62391 |

[15] | Perea, C.; Alcalá, J.; Yepes, V.; González-Vidosa, F.; Hospitaler, A., Design of reinforced concrete bridge frames by heuristic optimization, Advances in Engineering Software, 39, 676-688, (2008) |

[16] | Saribas, A.; Erbatur, F., Optimization and sensitivity of retaining structures, Journal of Geotechnical Engineering, 122, 649-656, (1996) |

[17] | Shi, Y.; Eberhart, R., A modified particle swarm optimizer, 69-73, (1998), Piscataway, USA |

[18] | van den Bergh, F., Engelbrecht, A.P., 2002. A New Locally Convergent Particle Swarm Optimizer. IEEE International Conference on Systems, Man and Cybernetics, Hammamet, Tunisia, p.96-101. |

[19] | Wang, Y., Reliability-based economic design optimization of spread foundations, Journal of Geotechnical and Geoenvironmental Engineering, 135, 954-959, (2009) |

[20] | Wang, Y.; Kulhawy, F. H., Economic design optimization of foundations, Journal of Geotechnical and Geoenvironmental Engineering, 134, 1097-1105, (2008) |

[21] | Xie, X.F., Zhang, W.J., Yang, Z.L., 2002. Adaptive Particle Swarm Optimization on Individual Level. 6th International Conference on Signal Processing, Beijing, China, p.1215-1218. |

[22] | Yepes, V.; Alcala, J.; Perea, C.; González-Vidosa, F., A parametric study of optimum Earth-retaining walls by simulated annealing, Engineering Structures, 30, 821-830, (2008) |

[23] | Zhong, W. M.; Li, S. J.; Qian, F., \(θ\)-PSO: a new strategy of particle swarm optimization, Journal of Zhejiang University-SCIENCE A, 9, 786-790, (2008) · Zbl 1142.90512 |

This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.