000			03178nas|a2200397 i 4500
005			20260818170727.0
008			041006s2004 th uzm rtt 00| a1eng d
035			_a.b11941881
099		9	_aAIT Thesis no.WM-03-05
100	1		_aDhanaseela, M. P. P.
245	1	0	_aOptimal design of pipe networks using a genetic algorithm
260			_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2004
300			_a1 v. (various pagings)
490	1		_aThesis ; _vno. WM-03-05
500			_aA thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering
502			_aThesis (M.Eng.) - Asian Institute of Technology, 2004
520			_aThe aim of this study is to develop a genetic based programme for pipe diameter optimization. The developed programme is applied to a case study, distribution system of Weligama water supply scheme in Sri Lanka. Then the performance of genetic algorithm is compared for cross validation with that of non linear programming. It is proven that the genetic algorithm method using the standard three operators is particularly effective in finding global optimal solution for the case study network. It should be noted that the genetic algorithm technique is ideally suited to discrete problems such as selection of commercially availably pipe sizes. Furthermore, water demand for the design is estimated and those demand data are input to the GA program. The output diameter values from the GA program are compared with the pipe diameters of existing distribution system. It is found that some of the existing pipe diameters will not be able to cater for the demand at year 2011. And at the same time, it is evident that 148 number of pipes in the existing distribution system have been over-estimated. The National Water Supply and Drainage Board in Sri Lanka designs pipe networks mainly not to violate the hydraulic constraints. Manual calculations followed by hydraulic simulations are carried out to find the suitable pipe network design. In this study, attempts have been made to obtain a pipe network, which satisfies hydraulics and the cost optimality.
650		0	_aWater-pipes _zSri Lanka
650		0	_aGenetic algorithms
700	0		_aTawatchai Tingsanchali, _eChairperson
700	0		_aManukid Parnichkun, _eExamination Committee
700	1		_aClemente, Roberto S., _eExamination Committee
710	2		_aRoyal Government of Netherland, _eScholarship donor
810	2		_aAsian Institute of Technology. _tThesis ; _vno. WM-03-05
856			_3Full-Text _u http://203.159.5.9/ait-thesis/detail.php?q=B09109
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