Document Type : Original Article

Authors

Abstract

The cost of concrete gravity dams is more than other dams, Therefore in order to make the project more economical, optimization of dimensions with aim of reducing the volume of concrete used, becomes a necessity. In this study keeping in view the sustainability situation, dimensions of Koyna concrete gravity dam was developed and optimized by using Honey Bee Mating Optimization model in the Matlab software. The results show that the volume of concrete used in the construction of this dam is equal to 3633 m3 for existing dimensions, and  Under optimal dimensions it declined to 3312.52 m3, which indicates a reduction of 8.82 percent in the objective function value (volume of concrete used in the construction of the dam). Therefore it can be concluded the reduced volume of concrete used for the construction of the dam makes a considerable saving on the costs of the project, and hence the project will be economical.

Keywords

Abbass, H. A. 2001. Marriage in Honey Bees Optimization (MBO): a haplometrosis polygynous swarming approach. The Congress on Evolutionary Computation. May 27-30. 1, 207-214.
 
Abrishami, J. 2001. Concrete Dams; Design and Performance. Astan-e-Qods Razavi Press. (in Persian)
 
Afshar, A., Bozorg-Haddad, O., Marino, M. A. and Adams, B. J. 2007. Honey Bee Mating Optimization (HBMO) algorithm for optimal reservoir operation. J. Franklin Instit. 344(5): 452-462.
 
Anon. 1976. Design of Gravity Dams. United States Department of the Interior Bureau of Reclamation (USBR). A Water Resources Technical Press. Colorado.
 
Anon. 1987. Design of Small Dams. United States Department of the Interior Bureau of Reclamation (USBR). 1987. A Water Resources Technical Press. Colorado.
 
Blum, C. and Roli, A. 2003. Metaheuristics in combinatorial optimization overview and conceptual comparision. ACM Comput. Surv. 35(3): 268-308.
 
Bozorg-Haddad, O., Afshar, A. and Marino, M. A. 2006. Honey Bee Mating Optimization (HBMO) algorithm: a new heuristic approach for water resources optimization. Water Resour. Manag. 20, 661-680.
 
Calayir, Y. and Karaton, M. 2005. A continuum damage concrete model for earthquake analysis. Soil Dyn. Earthq. Eng. 25(3): 857-869.
 
Carmen, S. and Popa, R. 2010. Application of honey-bees mating optimization algorithm to pumping station scheduling for water supply. Mech. Eng. 72(1): 77-84.
 

Dehghani, A. A., Montazer, Gh. A., Nasiri, F. and Ghodsian, M. 2006. Use of genetic algorithms and artificial neural network for optimization of concrete gravity dam sections. J. Modares Technic. Eng. 25, 99-112. (in Persian)

 
Esat, V. and Hall, M. J. 1994. Water resources system optimization using genetic algorithms. Proceeding of the First International Conference on Hydroinformatics. Balkema. Rotterdam. 1, 225-231.
 
Ghezel-Soufloo, A. and Deyminiyyat, A. 2010. Application of genetic algorithm in optimization of embankment dams: case study Hesar-Sangi dam in Birjand. Proceeding of the First National Conference on Applied Research of Water Resources. (in Persian)
 
Marinakis, Y., Marinaki, M. and Dounias, G. 2011. Honey Bees Mating Optimization algorithm for the euclidean traveling salesman problem. J. Info. Sci. 181(20): 4684-4698.
 
Teo, J. and Abbas, H. A. 2001. An Annealing approach to the mating flight trajectories in the marriage in Honey Bees Optimization algorithm. Technical Report CS04/01. School of Computer Science. University of New South Wales at ADFA.
 

Varaei, H. and Ahmadi-Nadoushan, B. 2008. Comparison of classic optimization techniques and intelligent in determining the optimum section of concrete gravity dams. Proceeding of the Fourth National Congress of Civil Engineering. University of Tehran. (in Persian)

 
Wardlaw, R. and Sharif, M. 1999. Evaluation of genetic algorithms for optimal reservoir system operation. J. Water Resour. Plann. Manage-ASCE. 125(1): 25-33.