000			02266cam a2200337 a 4500
003			EG-GiCUC
005			20250223031418.0
008			160128s2015 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aPh.D
099			_aCai01.20.02.Ph.D.2015.El.H
100	0		_aElshimaa Ahmed Ramadan Ibrahim Elgendi
245	1	2	_aA hybrid computational intelligent approach to solve project scheduling problems / _cElshimaa Ahmed Ramadan Ibrahim Elgendi ; Supervised Mohamed Hassan Rasmy , Omar Soliman Soliman
246	1	5	_aأسلوب حسابى ذكى مهجن لحل مشاكل جدولة المشروعِ
260			_aCairo : _bElshimaa Ahmed Ramadan Ibrahim Elgendi , _c2015
300			_a146 Leaves : _bcharts ; _c25cm
502			_aThesis (Ph.D.) - Cairo University - Faculty of Computers and Information - Department of Operations Research and Decision Support
520			_aMulti-mode resource-constrained project scheduling problem (MRCPSP) is one of the most important problems in the context of project scheduling. MRCPSP is a notoriously difficult problem in combinatorial optimization for which extensive investigation has been devoted to the development of efficient algorithms to find optimal or near-optimal solutions [7, 25, 30, 45]. Estimation of Distribution Algorithms (EDAs) are some of the most powerful evolutionary algorithms (EAs). The first motivation behind the emergence of EDAs, is to identify and exploit the linkage between variables in the solution in order to assist the evolution. Unlike other EAs, EDAs do not use crossover or mutation. Instead, they explicitly extract global statistical information from the previous search and build a posterior probability model of promising solutions, based on the extracted information
530			_aIssued also as CD
653		4	_aCombinatorial optimization on problem
653		4	_aComputational intelligence
653		4	_aMulti-mode resource-constrained project scheduling problems
700	0		_aMohamed Hassan Rasmy , _eSupervisor
700	0		_aOmar Soliman Soliman , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aAml _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c54767 _d54767