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Optimization model the pipe diameter in the drinking water distribution network using multi-objective genetic algorithm

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Under conditions of gravity flow, the performance of a distribution pipe network for drinking water supply can be measured by investment cost and the difference in real and target pressures at each node to ensure fairness of the service. Therefore, the objective function for the optimization in the design of a complex gravity flow pipe network is a multi-purpose equation system set up to minimize the above-mentioned two parameters. This article presents a new model as an alternative solution to solving the optimization equation system by combining the Newton–Raphson and genetic algorithm (GA) methods into a single unit so that the resulting model can work effectively. The Newton–Raphson method is used to solve the hydraulic equation system in pipelines and the GA is used to find the optimal pipe diameter combination in a network. Among application models in a complex pipe network consisting of 12 elements and 10 nodes, this model is able to show satisfactory performance. Considering variations in the value of the weighting factor in the objective function, opti-mal conditions can be achieved at the investment cost factor (ω1) = 0.75 and the relative energy equalization factor at the service node (ω2) = 0.25. With relevant GA input parameters, optimal conditions are achieved at the best fitness value of 1.016 which is equivalent to the investment cost of USD 56.67 thous. with an average relative energy deviation of 1.925 m.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
55--64
Opis fizyczny
Bibliogr. 23 poz., rys., tab.
Twórcy
autor
  • University of Muhammadiyah Malang, Faculty of Engineering, Jl. Raya Tlogomas No. 246, 65114, Malang, Indonesia
  • University of Muhammadiyah Malang, Faculty of Engineering, Jl. Raya Tlogomas No. 246, 65114, Malang, Indonesia
  • Mataram University, Faculty of Engineering, Mataram, Indonesia
Bibliografia
  • ABEBE A.J., SOLOMATINE D.P. 1998. Application of global optimization to the design of pipe networks. Proc. 3rd International Conference on Hydroinformatics. Copenhagen, August 1998. Balkema. Rotterdam p. 1–8.
  • AFSHAR M.H. 2006. Application of ant algorithm to pipe network optimization. Iranian Journal of Science & Technology. Transaction B, Engineering. Vol. 31. No. B5 p. 487–500.
  • AKLOG D., HOSOI Y. 2017. All-in-one model for designing optimal water distribution pipe networks. Journal of Engineering Drinking Water Engineering and Science. DOI 10.5194/dwes-10-33-2017.
  • ALI M.M., STOREY C. 1994. Modified controlled random search algorithms. International Journal of Computer Mathematics. Vol. 53. Iss. 3–4 p. 229–235.
  • BELLO A.D., WAHEED A., ALAYANDE, JOHNSON A.O., ISMAIL A, LAWAN U.F. 2015. Optimization of the designed water distribution system using MATLAB. International Journal of Hydraulic Engineering. Vol. 4(2) p. 37–44. DOI 10.5923/j.ijhe. 20150402.03.
  • GOLDBERG D.E. 1989. Genetic algorithms in search, optimization & machine learning. Addison-Wesley Publishing Co., Reading. ISBN 0201157675 pp. 432.
  • KADU M.S., GUPTA R., BHAVE P.R. 2008. Optimal design of water networks using a Modified Genetic Algorithm with reduction in search space. Journal of Water Resources Planning and Management. Vol. 134(2) p. 147–159.
  • KUMAR D., SUDHEER C.H., MATHUR S., ADAMOWSKI J. 2015. Multi-objective optimization of in-situ bioremediation of groundwater using a hybrid metaheuristic technique based on differential evolution, genetic algorithms and simulated annealing. Journal of Water and Land Development. No. 27 p. 29–40. DOI 10.1515/jwld-2015-0022.
  • MEMON K.K., NARUKLAR S.N. 2016. Review of pipe sizing optimization by Genetic Algorithm. IJIRST – International Journal for Innovative Research in Science & Technology. Vol. 3. Iss. 06 p. 138–141.
  • MOOSAVIAN N., JAEFARZADEH R. 2014. Hydraulic analysis of water supply networks using a modified Hardy Cross method. International Journal of Engineering, Transactions B: Applications. Vol. 27. No. 9 p. 1331–1338. DOI 10.5829/idosi. ije.2014.27.09c.02.
  • MTOLERA I., HAIBIN L., YE L., FENG S.B., XUE D., YI M. 2014. Optimization of tree pipe networks layout and size using Particle Swam Optimization. WSEAS Transactions on Computers. Vol. 13 p. 219–230.
  • PRICE W.L. 1983. Global optimization by controlled random search. Journal of Optimization Theory & Applications. Vol. 40 p. 333–348. DOI 10.1007/BF00933504.
  • RAJABPOUR R., TALEBBEYDOKHTI N. 2014. Simultaneous layout and pipe size optimization of pressurized irrigation networks. Basic Research Journal of Agricultural Science and Review. Vol. 3(12) p. 131–145.
  • SALEH C., SULIANTO 2011. Optimization diameter of pipe at fresh water network system. Journal of Academic Research International. Vol. 01. Iss. 02. No. 2 p. 103–109.
  • SÂRBU I. 2010. Optimization of water distribution networks. Proceeding of the Romanian Academy. Ser. A. Vol. 11. No. 4 p. 330–339.
  • SÂRBU I. 2011. Nodal analysis models of looped water distribution networks. ARPN Journal of Engineering and Applied Sciences. Vol. 6. No. 8 p. 115–125.
  • SHIVATAVA M., PRASAD V., KHARE R. 2015. Multi-objective optimization of water distribution system using particle swarm optimization. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE). Vol. 12. Iss. 6. Ver. I p. 21–28.
  • SOETOPO W., SUHARDJONO, ANDAWAYANTI U., SAYEKTI R.W., ISMOYO J. 2018. The comparison study for the models of reservoir release rule for irrigation. Case study: Sutami reservoir. Journal of Water and Land Development. No. 36 p. 153–160. DOI 10.2478/jwld-2018-0015.
  • SOLOMATINE D.P. 1998. Genetic and other global optimization algorithms – compareson and use in calibration problems. Proc. 3rd Intern. Conference on Hydroinformatics Copenhagen, August 1998. Balkema, Rotterdam p. 1021–1028.
  • SOMAIDA M., ELZAHAR M., SHARAAN M. 2011. A suggestion of optimization process for water pipe networks design. International Conference on Environment and BioScience IPCBEE. Vol. 21 p. 68–73.
  • SULIANTO 2015a. Programasi linier untuk pencarian diameter pipa optimal pada sistem jaringan pipa distribusi air bersih [Linear programming for search optimum diameter pipe in network pipe open in water supply system]. Journal of Media Teknik Sipil. Vol. 13. No. 1 p. 91–98.
  • SULIANTO 2015b. Pencarian diameter optimum pada sistim jaringan pipa terbuka dengan algoritma genetik. Di: Prosiding Seminar Nasional Teknik Sipil [The search optimum diameter on open network pipe system using GA. In: Proceeding National Conference Civil Engineering]. Program Studi Pasca Sarjana Teknik Sipil dan Perencanaan XI 2015 p. 191–204.
  • SULIANTO, BISRI M., LIMANTARA L.M., SISINGGIH D. 2018. Automatic calibration and sensitivity analysis of DISPRIN model parameters: A case study on Lesti watershed in East Java, Indonesia. Journal of Water and Land Development. No. 37 p. 141–152. DOI 10.2478/jwld-2018-0033.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-48f18f7f-adf9-4d42-807a-1d0f7be27fa4
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