طراحی بهینه شبکه‌های جمع‌آوری سیلاب شهری با استفاده از الگوریتم ژنتیک تطبیقی

نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیئت علمی/ دانشگاه گیلان - گروه مهندسی آب

2 استاد، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه شهید چمران اهواز

3 دانشیار، گروه مهندسی عمران، دانشکده مهندسی، دانشگاه شهید چمران اهواز

چکیده

در این پژوهش برای طراحی بهینه شبکه­های جمع­آوری سیلاب شهری که از زیرساخت­های مهم و ضروری شهرها محسوب می­شوند، یک الگوریتم ژنتیک تطبیقی توسعه داده شد. برای بهره­گیری از ظرفیت ذخیره­سازی ذاتی شبکه، قید جریان با سطح آزاد با قید عدم سیل­گیری جایگزین و برای شبیه­سازی هیدرولیکی شبکه، از مدل SWMM 5.1 بهره­گیری شد. رویکرد پیشنهادی، یک روش طراحی بهینه مبتنی بر هیدروگراف است که در آن برای روندیابی جریان در مجاری شبکه از مدل موج کامل دینامیکی استفاده می­شود. روش پیشنهادی برای طراحی بهینه شبکه جمع­آوری سیلاب در منطقه کیانپارس شهر اهواز مورد استفاده قرار گرفت و نتایج آن با نتایج روش مرسوم )طراحی بهینه­ با قید جریان با سطح آزاد(، مقایسه شد. نتایج نشان داد که الگوریتم توسعه­داده شده از سرعت و راندمان بالایی برخوردار است. به­علاوه بهره­گیری از ظرفیت ذخیره­سازی ذاتی شبکه باعث شد تا هزینه ساخت جواب بهینه رویکرد پیشنهادی (885/474 میلیارد ریال) نسبت به هزینه جواب بهینه روش مرسوم (686/968 میلیارد ریال) به کمتر از نصف تقلیل یابد.

کلیدواژه‌ها


عنوان مقاله [English]

Optimal Design of Storm Sewer Networks Using Adaptive Genetic Algorithm

نویسندگان [English]

  • Sayyed Ali Moussavi 1
  • Hossein Mohammad Vali Samani 2
  • Ali Haghighi 3
1 Faculty member/University of guilan- Water engineering group
2 Professor, Civil Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz
3 Assistant Professor, Civil Engineering Department, Faculty of Engineering, Shahid Chamran University of Ahvaz
چکیده [English]

In this study for optimal design of storm sewer networks, as an essential urban infrastructure, an adaptive genetic algorithm was developed. In order to utilize the intrinsic storage capacity of the sewer network, the free surface flow constraint was replaced with a new constraint in which no surface flooding was allowed. Furthermore, for the hydraulic simulation of the candidate sewer network, the Storm Water Management Model (SWMM 5.1) was used. The proposed framework was a hydrograph-based optimal design method in which the full dynamic wave model was used for flow routing in the network conduits. The proposed approach was applied for the optimal design of Kianpars storm sewer network, a suburb of Ahvaz city, in Iran. The results were compared with those obtained by the conventional optimal design method (with free surface flow constraint). The comparison showed that the developed algorithm had a high speed and efficiency. Furthermore, the proposed framework (with optimal solution’s construction cost of 474.885 Billion Rials) by utilizing the intrinsic storage capacity of the network could reduce the network construction cost to less than a half of the conventional method cost (with optimal solution’s construction cost of 968.686 Billion Rials).

کلیدواژه‌ها [English]

  • Adaptive genetic algorithm
  • Constraint handling
  • Optimal design
  • optimization
  • Storm sewer network
Afshar M, 2006. Application of a genetic algorithm to storm sewer network optimization. Scientia Iranica 13: 234-244.
Afshar M, 2010. A parameter free continuous ant colony optimization algorithm for the optimal design of storm sewer networks: Constrained and unconstrained approach. Advances in Engineering Software 41: 188-195.
Afshar MH, Afshar A, Mariño MA and Darbandi AAS, 2006. Hydrograph-based storm sewer design optimization by genetic algorithm. Canadian Journal of Civil Engineering 33: 319-325.
Butler D and Davies J, 2010. Urban Drainage. CRC Press.
Eshleman L and Shaffer DJ, 1993. Real-Coded Genetic Algorithms and Interval-Schemata. Pp. 187-202. In: Whitley LD (ed). Foundations of Genetic Algorithms. Morgan Kaufmann, San Mateo,CA.
Farmani R, Savic DA and Walters GA, 2006. A hybrid technique for optimization of branched urban water systems. Pp. 985-992. Proceedings of the 7th International Conference on Hydroinformatics. Nice, France.
Gen M and Cheng R, 2000. Genetic Algorithms and Engineering Optimization. John Wiley & Sons, New York.
Guo Y, Keedwell EC, Walters GA and Khu ST, 2007a. Hybridizing cellular automata principles and NSGAII for multi-objective design of urban water networks. Pp. 546-559. Proceedings of the Evolutionary Multi-Criterion Optimization. Sendai, Japan.
Guo Y, Walters GA, Khu ST and Keedwell EC, 2007b. A novel cellular automata based approach to storm sewer design. Engineering Optimization 39: 345-364.
Guo Y, Walters GA and Savic D, 2008. Optimal design of storm sewer networks: Past, present and future. Pp. 1-10. Proceedings of the 11th International Conference on Urban Drainage. Edinburgh, Scotland.
Haupt RL and Haupt SE, 2004. Practical Genetic Algorithms. John Wiley & Sons, Hoboken, New Jersey.
Heaney JP, Sample D, Wright L and Fan C, 2002. Costs of Urban Stormwater Control EPA-600/R-02/021. US Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, Cincinnati.
Kuo JT, Yen BC and Hwang GP, 1991. Optimal design for storm sewer system with pumping stations. Journal of Water Resources Planning and Management 117: 11-27.
Liang LY, Thompson RG and Young DM, 2004. Optimising the design of sewer networks using genetic algorithms and tabu search. Engineering Construction and Architectural Management 11: 101-112.
Mays LW and Yen BC, 1975. Optimal cost design of branched sewer systems. Water Resources Research 11:37-47.
Miles SW and Heaney JP, 1988. Better than “Optimal” method for designing drainage systems. Journal of Water Resources Planning and Management 114: 477-499.
Moeini R and Afshar MH, 2012. Layout and size optimization of sanitary sewer network using intelligent ants. Advances in Engineering Software 51: 49-62.
Muleta MK and Boulos PF, 2007. Multiobjective optimization for optimal design of urban drainage systems. Pp. 1-10. Proceedings of the World Environmental and Water Resources Congress 2007: Restoring Our Natural Habitat. Tampa, Florida.
Palumbo A, Cimorelli L, Covelli C, Cozzolino L, Mucherino C and Pianese D, 2014. Optimal design of urban drainage networks. Civil Engineering and Environmental Systems 31: 79-96.
Robinson DK and Labadie JW, 1981. Optimal Design of Urban Storm Water Drainage Systems. University of Kentucky, Lexington, KY, USA.
Rossman LA, 2015. Storm Water Management Model User's Manual, Version 5.1. U.S. Environmental Protection Agency, Office of Research and Development, National Risk Management Research Laboratory, Cincinnati, OH.
Sun S, Djordjevic S and Khu S, 2011a. Decision making in flood risk based storm sewer network design. Water Science and Technology 64: 247-254.
Sun S, Djordjevic S and Khu S, 2011b. A general framework for flood risk-based storm sewer network design. Urban Water Journal 8: 13-27.
USEPA,  2000. Collection Systems Technology Fact Sheet: Sewers Lift Station. Collection Systems Technology Fact Sheet EPA 832-F-00-073. United States Environmental Protection Agency, Washington, D.C.
Walters GA and Lohbeck T, 1993. Optimal layout of tree networks using genetic algorithms. Engineering Optimization 22: 27-48.