000			05253namaa22004211i 4500
003			OSt
005			20250223033343.0
008			241211s2023 |||a|||fr|m|| 000 0 eng d
040			_aEG-GICUC _beng _cEG-GICUC _dEG-GICUC _erda
041	0		_aeng _beng _bara
049			_aDeposit
082	0	4	_a627
092			_a627 _221
097			_aM.Sc
099			_aCai01.13.05.M.Sc.2023.Ya.M
100	0		_aYasmen Amr Hamed Elsaid Khalil, _epreparation.
245	1	2	_aA Modified Genetic Algorithm-Heuristic Programming Model For Optimal Design Of Sewer Networks / _cby Yasmen Amr Hamed Elsaid Khalil ; Under the Supervision of Prof. Ashraf Hassan Mohib Ghanem, Dr. Yehya Emad Imam
246	1	5	_aنموذج معدل بخوارزمية جينية مع برمجة مباشرة لتحقيق التصميم الأمثل لشبكات الصرف الصحي /
264		0	_c2023.
300			_a106 pages : _billustrations ; _c30 cm. + _eCD.
336			_atext _2rda content
337			_aUnmediated _2rdamedia
338			_avolume _2rdacarrier
502			_aThesis (M.Sc.)-Cairo University, 2023.
504			_aBibliography: pages 50-52.
520			_aAmong the Sustainable Development Goals (SDGs) established by the United Nations, SDG 6 requires water and sanitation for all. However, construction of wastewater collection systems requires considerable investments. These investments can be reduced by using automated optimization tools for identifying the optimal design alternative that achieves minimal system cost while satisfying design constraints. Much of the related research over the past decade has focused on developing optimization design tools that are more robust and efficient. Therefore, there is a need to develop an efficient tool for obtaining the optimum design of the sewage systems with reasonable computational effort. In this study, a recent hybrid optimization model that was introduced by Hassan et al. (2018) and relies on Genetic Algorithm (GA) and Heuristic Programming (HP), was modified to improve efficiency by reducing runtime and the number of computations. Similar to the original GA-HP model, the Modified GA-HP (MGAHP) model identifies optimal pipe diameters and slopes by minimizing the total cost of gravity sewers and manholes depths for a selected system layout. The MGAHP model greatly reduces the extensive computational calculations, checks, and associated penalty costs that are applied in the original GA-HP model by initially limiting the set of feasible diameters for individual sewer lines. The efficiency of the proposed model was tested using four case studies ranging in size from 12 to 40 sewers. In the first case study with 12 pipes, the modified model required on average ~17% less function evaluations for the Genetic Algorithm and reduced the overall runtime by 98%. In the second case study with 20 pipes, the modified model required 10% less GA function evaluations and reduced the overall runtime by 98.2%. In the third case study with 40 pipes, the modified model required 52% less GA function evaluations and reduced the overall runtime by 99%. The fourth example was solved using Bentley SewerGems, GA-HP model and MGAHP model. In the fourth case study with 20 pipes, the modified model required 14% less GA function evaluations and reduced the overall runtime by 97%. The cost of the SewerGems design is 17.7 % higher than the design achieved by GA-HP model and MGAHP model. The efficiency of the proposed model enables its reliable application for optimal design of large sewer networks and for examining an extensive set of possible layouts
520			_aيهدف هذا البحث الى تقديم نموذج معدل بخوارزمية جينية مع برمجة مباشرة لتحقيق التصميم الامثل لشبكات الصرف الصحي، هذا النموذج هو نموذج تم تطويره من نموذج تم تقديمه في Hassan et al. (2018). تم تطوير النموذج الأصلي لتحسين الكفاءة عن طريق تقليل نطاق البحث وذلك بتحديد مجموعة من الاقطار لكل ماسورة في البداية و استبعاد بعض الأقطار التي لا تحقق القيم التصميمية المقبولة من سرعات و نسب امتلاء. يهدف النموذج المقدم الى الوصول الى التصميم الأمثل بكفاءة عالية و يقلل النموذج المقدم بشكل كبير من الحسابات و بالتالي فهو أسرع من النموذج الأصلي.
530			_aIssued also as CD
546			_aText in English and abstract in Arabic & English.
650		7	_aIrrigation and Hydraulics _2qrmak
653		0	_aOptimal design _aSewer Network _aHeuristic Programming _aWastewater _aManagement _aOptimization
700	0		_aAshraf Hassan Mohib Ghanem _ethesis advisor.
700	0		_aYehya Emad Imam _ethesis advisor.
900			_b01-01-2023 _cAshraf Hassan Mohib Ghanem _cYehya Emad Imam _dHesham Bekhit Mohammed _dAnas Mohammed El Molla _UCairo University _FFaculty of Engineering _DDepartment of Irrigation and Hydraulics Engineering
905			_aEman _eHuda
942			_2ddc _cTH _e21 _n0
999			_c169405