Distributed Hybrid Genetic Algorithms for Structural Optimization on a PC Cluster
Publication: Journal of Structural Engineering
Volume 132, Issue 12
Abstract
Even though several genetic algorithm (GA)-based optimization algorithms have been successfully applied to complex optimization problems in various engineering fields, such methods are computationally too expensive for practical use in the field of structural optimization, particularly for large-scale problems. Furthermore, the successful implementation of GA-based optimization algorithm requires a cumbersome routine through trial-and-error for tuning the GA parameters that are different depending on each problem. Therefore, to overcome these difficulties, a high-performance GA is developed in the form of a distributed hybrid genetic algorithm for structural optimization, implemented on a cluster of personal computers. The distributed hybrid genetic algorithm proposed in this paper consists of a -GA running on a master computer and multiple simple GAs running on slave computers. The algorithm is implemented on a PC cluster and applied to the minimum weight design of steel structures. The results show that the computation time required for GA-based optimization can be drastically reduced and the problem-dependent parameter tuning process can be avoided.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This material is based on work supported by the Ministry of Construction and Transportation of Korea (Grant No. UNSPECIFIEDC103A1040001-03A0204-00210) and research fund of the National Research Laboratory Program (Project No. KMST2005-01504) from the Ministry of Science and Technology.
References
Adeli, H., and Cheng, N. T. (1993). “Integrated genetic algorithm for optimization of space structures.” J. Aerosp. Eng., 6(4), 315–328.
Adeli, H., and Park, H. S. (1998). Neurocomputing for design automation, CRC, Boca Raton, Fla.
AISC (1989). Manual of steel construction, Allowable stress design, Chicago.
Architectural Institute of Korea (AIK). (2000). Standard design loads for buildings, Seoul, Korea.
Arora, J. S. (1989). Introduction to optimum design, McGraw–Hill, New York.
Balla, M. C., and Lingireddy, S. (2000). “Distributed genetic algorithm model on network of personal computers.” J. Comput. Civ. Eng., 14(3), 199–205.
Camp, C., Pezeshk, S., and Cao, G. (1998). “Optimized design of two-dimensional structures using genetic algorithm.” J. Struct. Eng., 124(5), 551–559.
Chen, T. Y., and Chen, C. J. (1997). “Improvement of simple genetic algorithms in structural design.” Int. J. Numer. Methods Eng., 40(7), 1323–1334.
De Jong, K. A. (1975). “An analysis of the behavior of a class of genetic adaptive systems.” Doctoral dissertation, The Univ. of Michigan, Ann Arbor, Mich.
Eiben, A. E., Hinterding, R., and Michalewicz, Z. (1999). “Parameter control in evolutionary algorithms.” IEEE Trans. Evol. Comput., 3(2), 124–141.
Foley, C. M., and Schinler, D. (2003). “Automated design of steel frames using advanced analysis and objected-oriented evolutionary computation.” J. Struct. Eng., 129(5), 648–660.
Goldberg, D. E. (1989). Genetic algorithms in search, optimization and machine learning, Addison-Wesley, Reading, Mass.
Jitendra, A., and Mathew, T. V. (2004). “Transit route network design using parallel genetic algorithm.” J. Comput. Civ. Eng., 18(3), 248–256.
Kamal, C. S. (2001). “Bilevel parallel genetic algorithms for optimization of large steel structures.” Comput. Aided Civ. Infrastruct. Eng., 16(5), 295–304.
Kocer, F. Y., and Arora, J. S. (1997). “Standardization of steel pole design using discrete optimization.” J. Struct. Eng., 123(3), 345–349.
Koumousis, V. K., and Georgiou, P. G. (1994). “Genetic algorithms in discrete optimization of steel truss roofs.” J. Comput. Civ. Eng., 8(3), 309–325.
Krishnakumar, K. (1989). “Micro-genetic algorithms for stationary and non-stationary function optimization.” Proc. SPIE, 1196, 282–296.
MPI Forum (1995). A message passing interface standard, Univ. of Tennessee, Knoxville, Tenn.
Park, H. S., and Sung, C. W. (2002). “Optimization of steel structures using distributed Simulated annealing algorithm on a cluster of personal computers.” Comput. Struct., 80(15), 1305–1316.
Pezeshk, S., Camp, C. V., and Chen, D. (2000). “Design of nonlinear framed structures using genetic optimization.” J. Struct. Eng., 126(3), 382–388.
Pham, D. T., and Karaboga, D. (2000). Intelligent optimization techniques, Springer, New York.
Rajan, S. D. (1995). “Sizing, shape, and topology design optimization of trusses using genetic algorithm.” J. Struct. Eng., 121(10), 1480–1487.
Rajeev, S., and Krishnamoorthy, C. S. (1992). “Discrete optimizationof structures using genetic algorithms.” J. Struct. Eng., 118(5), 1233–1250.
Rajeev, S., and Krishnamoorthy, C. S. (1997). “Genetic algorithms-based methodologies for design optimization of trusses.” J. Struct. Eng., 123(3), 350–358.
Soh, C. K., and Yang, J. (1996). “Fuzzy controlled genetic algorithm search for shape optimization.” J. Comput. Civ. Eng., 10(2), 143–150.
Wongprasert, N., and Symans, M. D. (2004). “Application of a genetic algorithm for optimal damper distribution within the nonlinear seismic benchmark building.” J. Eng. Mech., 130(4), 401–406.
Zhu, D. M. (1986). “An improved Templeman’s algorithm for optimum design of trusses with discrete member sizes.” Eng. Optimiz., 9(3), 303–312.
Information & Authors
Information
Published In
Journal of Structural Engineering
Volume 132 • Issue 12 • December 2006
Pages: 1890 - 1897
Copyright
© 2006 ASCE.
History
Received: Feb 3, 2005
Accepted: Apr 19, 2006
Published online: Dec 1, 2006
Published in print: Dec 2006
Notes
Note. Associate Editor: Sherif El-Tawil
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.