Optimal Design of Gravity Pipeline Systems Using Genetic Algorithm and Mathematical Optimization

Document Type : Research Paper

Authors

1 PhD Student of Water and Environmental Eng., Iran University of Science and Tech., Tehran

2 Assoc. Prof., Dept. of Civil Eng., Iran University of Science and Tech., Tehran

Abstract

In recent years, the optimal design of pipeline systems has become increasingly important in the water industry. In this study, the two methods of genetic algorithm and mathematical optimization were employed for the optimal design of pipeline systems with the objective of avoiding the water hammer effect caused by valve closure. The problem of optimal design of a pipeline system is a constrained one which should be converted to an unconstrained optimization problem using an external penalty function approach in the mathematical programming method. The quality of the optimal solution greatly depends on the value of the penalty factor that is calculated by the iterative method during the optimization procedure such that the computational effort is simultaneously minimized. The results obtained were used to compare the GA and mathematical optimization methods employed to determine their efficiency and capabilities for the problem under consideration. It was found that the mathematical optimization method exhibited a slightly better performance compared to the GA method.

Keywords

Main Subjects

References

1. Lansey, K. E., and Mays, L. W., (1989). “Optimization model for water distribution system design.” J. Hydraul. Eng., 115 (10), 1401-1418.
2. Simpson, A. R., Dandy, G. C., and Murphy, L. J. (1994). “Genetic algorithms compared to other techniques for pipe optimization.” J. of Water Resources Planning and Management, 120 (4), 423-443.
3. Savic, D. A., and Walters, G. A. (1997).“Genetic algorithms for least-cost design of water distribution networks.” J. of Water Resources Planning and Management, 123(2), 67-77.
4. Jung, B. S., and Karney, B. W., (2003). “Optimum selection of Hydraulic Devices for Water Hammer Control in the Pipeline Systems Using Genetic Algorithm.” Proceedings of ASME FEDSM’03, 4th ASME_JSME Joint Fluids Engineering Conference, Honolulu, Hawaii, USA.
5. Jung, B. S., and Karney, B. W. (2004). “Fluid transients and pipeline optimization using GA and PSO: The diameter connection.” Urban Water, 1(2), 167-176.
6. Jung, B. S., and Karney, B. W. (2006). “Hydraulic optimization of transient protection devices using GA and PSO approaches.” J. of Water Resources Planning And Management, 132(1), 44-52.
7. Afshar, M. H., Akbari, M., and Marino, M. A. (2005). “Simultaneous layout and size optimization of water distribution networks: Engineering approach.” J. of Infrastructure Systems,  11(4), 221-230.
8. Malekpour, A., Karney, B. W., and Adams, B. J., (2007). “Improvement of the Yazd water conveyance control system by GA optimization.” Proceedings of the IASTED International Conference on Water Resources Management, 170-175.
9. Khale, R. V., Singh, R. P., and Mahar, P. S. (2008). “Optimal design of pressurized irrigation subunit.” Journal of Irrigation and Drainage Engineering, 134, (2), 137-146.
10. Vanderplaats, Miura and Associates. (1994). <Http://www.vander.com.>

11. Afshar, M. H., Afshar, A. and Marino, M. A. (2009). “An iterative penalty method for the optimal design of pipe networks.” International Journal of Civil Engineering, 7(2), 109-123.

12. Goldberg, D. E. (1989). Genetic algorithms in search optimization and machine learning, Reading, MA: Addison-Wesley, Longman Pub. Co., Inc., Boston, USA.
13. Chaudhry, M. H. (1979). Applied hydraulic transients, Van Nostrand Reinhold, New York.
Journal of Water and Wastewater; Ab va Fazilab ( in persian )
Volume 26, Issue 1 - Serial Number 1
serial number: 95
March and April 2015
Pages 107-118

Files

Share

How to cite

Statistics