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http://dx.doi.org/10.11001/jksww.2013.27.4.413

Field Application of Least Cost Design Model on Water Distribution Systems using Ant Colony Optimization Algorithm  

Park, Sanghyuk (University of Seoul)
Choi, Hongsoon (Korea Water and Wastewater Works Association)
Koo, Jayong (University of Seoul)
Publication Information
Journal of Korean Society of Water and Wastewater / v.27, no.4, 2013 , pp. 413-428 More about this Journal
Abstract
In this study, Ant Colony Algorithm(ACO) was used for optimal model. ACO which are metaheuristic algorithm for combinatorial optimization problem are inspired by the fact that ants are able to find the shortest route between their nest and food source. For applying the model to water distribution systems, pipes, tanks(reservoirs), pump construction and pump operation cost were considered as object function and pressure at each node and reservoir level were considered as constraints. Modified model from Ostfeld and Tubaltzev(2008) was verified by applying 2-Looped, Hanoi and Ostfeld's networks. And sensitivity analysis about ant number, number of ants in a best group and pheromone decrease rate was accomplished. After the verification, it was applied to real water network from S water treatment plant. As a result of the analysis, in the Two-looped network, the best design cost was found to $419,000 and in the Hanoi network, the best design cost was calculated to $6,164,384, and in the Ostfeld's network, the best design cost was found to $3,525,096. These are almost equal or better result compared with previous researches. Last, the cost of optimal design for real network, was found for 66 billion dollar that is 8.8 % lower than before. In addition, optimal diameter for aged pipes was found in this study and the 5 of 8 aged pipes were changed the diameter. Through this result, pipe construction cost reduction was found to 11 percent lower than before. And to conclusion, The least cost design model on water distribution system was developed and verified successfully in this study and it will be very useful not only optimal pipe change plan but optimization plan for whole water distribution system.
Keywords
ACO; Least Cost Design; Water distribution system; Water distribution networks analysis;
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  • Reference
1 Cunha, M. and Sousa, J. (1999) Water distribution network design optimization: simulated annealing approach, Journal of water resources planning and management, 125(4), pp. 215-221.   DOI
2 Alperovits, E. and Shamir, U. (1977) Design of optimal water distribution systems, Water resources research, 13(6), pp. 885-900.   DOI   ScienceOn
3 Bullnheimer, B., Hartl, R. F. and Strauss, C. (1997) A new rank based version of the Ant System: A computational study, Central european journal for operations research and economics, 7(1), pp. 25-38.
4 Cembrowicz, R. G. (1992) Water supply systems optimization for developing countries, Pipeline systems. Springer Netherlands, pp. 59-76.
5 Dandy, G. C., Simpson, A. R. and Murphy, L. J. (1996) An improved genetic algorithm for pipe network optimization, Water resources research, 32(2), pp. 449-458.   DOI
6 Hong, M. D., Yu, Y. H. and Jo, G. S. (2010) An ant colony optimization heuristic to solve the VRP with time window, Journal of korea information processing systems, 17-B(5), pp. 389-398
7 Eusuff, M. M. and Lansey, K. E. (2003) Optimization of water distribution network design using shuffled frog leaping algorithm, Journal of water resources planning and management, 129(3), pp. 210-225.   DOI   ScienceOn
8 Geem, Z. W. (2006) Optimal cost design of water distribution networks using harmony search, Engineering optimization, 38(3), pp. 259-277.   DOI   ScienceOn
9 Gupta, I., Gupta, A. and Khanna, P. (1999) Genetic algorithm for optimization of water distribution systems, Engineering modelling & software, 14, pp. 437-446.   DOI   ScienceOn
10 Ko, S. K., Oh, M. H. and Ahn, D. S. (1992) Application of a multiobjective technique for the optimum operation of pumps and reservoirs in service water transmission systems, Journal of korean society of water and wastewater, 1, pp. 8-18
11 Liong, S. Y. and Atiquzzaman, M. (2004) Optimal design of water distribution network using shuffled complex evolution, Journal of the institution of engineers, Singapore, 44(1), pp. 93-107.
12 Loganathan, G. V., greene, J. J. and Ahn, T. J. (1995) Deisign heuristic for global minimum cost water-distribution systems, Journal of water resources planning and management, 121(2), pp. 182-192.   DOI   ScienceOn
13 Maier, H. R., Simpson, A. R., Zecchin, A. C., Foong, W. K., Phang, K. Y., Seah, H. Y. and Tan, C. L. (2003) Ant colony optimization for design of water distribution systems, Journal of Water resources planning and management, 129(3), pp. 200-209   DOI   ScienceOn
14 Morely , M. S., Atkinson, R. M., Savic, D. a. and Walters, G. A. (2001) GAnet: genetic algorithm platform for pipe network optimisation, Advances in engineering software, 32(6), pp. 467-475.   DOI   ScienceOn
15 Savic, D. A. and Walters, G. A. (1997) Genetic algorithms for least-cost design of water distribution networks, Journal of water resources planning and management, 123(2), pp. 67-77.   DOI   ScienceOn
16 Morgan , D. R. and Goulter, I. C. (1985) Optimal urban water distribution design, Water resources research, 21(5), pp. 642-652.   DOI   ScienceOn
17 Ostfeld , A. and Tubaltzev, A. (2008) Ant colony optimization for least-cost design and operation of pumping water distribution systems, Journal of water resources planning and management, 134(2), pp. 107-118   DOI   ScienceOn
18 Tospornsampan, J., Kita, I., Ishii, M. and Kitamura, Y. (2007) Split-pipe design of water distribution network using simulated annealing, World Academy of Science, Engineering and Technology, 4, pp. 382-392.
19 Quindry, G. E., Liebman, J. C. and Brill, E. D. (1981) Optimization of looped-water distribution systems, Journal of the environmental engineering, 107(4), pp. 665-679.
20 Schaake, J. C., Lai, D. and Lai, F. H. (1969) Linear programming and dynamic programming application to water distribution network design, Rep. No. 116, Dept. of Civil Engineering, Massachusetts Institute of Technology, Cambridge, Mass
21 Vairamoorthy, K. and Ali, M. (2005) Pipe index vector : A method to improve genetic-algorithm- based pipe optimization, Journal of hydraulic engineering, 131(12) pp. 1117-1125.   DOI   ScienceOn
22 Van Dijk, M., Van Vuuren, S. J. and Van Zyl, J. E. (2008) Optimizing water distribution systems using a weighted penalty in a genetic algorithm, Water SA, 34(5), pp. 537-548.
23 Vasan A. and Simonovic, S. P. (2010) Optimization of water distribution network design using differential evolution, Journal of water resources planning and management, 136(2), pp. 279-287.   DOI   ScienceOn
24 Simpson, A. r., dandy, G. C. and Murphy, L. J. (1994) Genetic algorithm compared to other techniques for pipe optimization, Journal of water resources planning and management, 120(4), pp. 423-443.   DOI   ScienceOn
25 Wu, Z . Y. and Walski, T. (2005) Self-adaptive penalty approach compared with other constraint-handling techniques for pipeline optimization, Journal of water resources planning and management, 131(3), 181-192.   DOI   ScienceOn