000			05725cam a2200673 a 4500
001			ocn852150965
003			OCoLC
005			20241010112205.0
006			m d
007			cr cnu---unuuu
008			130708s2013 nju ob 000 0 eng d
010			_z 2013012700
040			_aN$T _beng _epn _cN$T _dOCLCO _dYDXCP _dDEBSZ _dOCLCA _dE7B _dCDX _dOCLCQ _dOCLCO _dGGVRL _dNKT _dLOA _dOCLCF _dOCLCQ _dTOA _dAGLDB _dMOR _dCCO _dPIFAG _dOCLCQ _dUUM _dOCL _dJBG _dSTF _dWRM _dVTS _dNRAMU _dOCLCQ _dAU@ _dUKAHL _dOCLCQ _dUKCRE _dOCLCQ _dOCLCO _dOCLCQ _dQGK _dOCLCO
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020			_a9789814513012 _q(electronic bk.)
020			_a9814513016 _q(electronic bk.)
020			_z9789814513005
020			_z9814513008
035			_a605588 _b(N$T)
035			_a(OCoLC)852150965 _z(OCoLC)960205435 _z(OCoLC)961540598 _z(OCoLC)962679427 _z(OCoLC)988437536 _z(OCoLC)991953643 _z(OCoLC)1037704474 _z(OCoLC)1038695202 _z(OCoLC)1045470998 _z(OCoLC)1153526817 _z(OCoLC)1259157473
050		4	_aTA343 _b.S76 2013eb
072		7	_aSCI _x064000 _2bisacsh
072		7	_aTEC _x029000 _2bisacsh
082	0	4	_a003/.83 _223
049			_aMAIN
245	0	0	_aStochastic Simulation Optimization for Discrete Event Systems : _bPerturbation Analysis, Ordinal Optimization, and Beyond / _cedited by Chun-Hung Chen (George Mason University, USA), Qing-Shan Jia (Tsinghua University, China) & Loo Hay Lee (National University of Singapore, Singapore).
260			_a[Hackensack] New Jersey : _bWorld Scientific, _c2013.
300			_a1 online resource
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
520			_a"Discrete event systems (DES) have become pervasive in our daily life. Examples include (but are not restricted to) manufacturing and supply chains, transportation, healthcare, call centers, and financial engineering. However, due to their complexities that often involve millions or even billions of events with many variables and constraints, modeling of these stochastic simulations has long been a "hard nut to crack". The advance in available computer technology, especially of cluster and cloud computing, has paved the way for the realization of a number of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and developed by Professor Y.C. Ho and his team; namely perturbation analysis and ordinal optimization for stochastic simulation optimization, and present the state-of-the-art technology, and their future research directions. Contents: Part I: Perturbation Analysis: IPA Calculus for Hybrid Systems; Smoothed Perturbation Analysis: A Retrospective and Prospective Look; Perturbation Analysis and Variance Reduction in Monte Carlo Simulation; Adjoints and Averaging; Infinitesimal Perturbation Analysis in On-Line Optimization; Simulation-based Optimization of Failure-Prone Continuous Flow Lines; Perturbation Analysis, Dynamic Programming, and Beyond; Part II: Ordinal Optimization : Fundamentals of Ordinal Optimization; Optimal Computing Budget Allocation; Nested Partitions; Applications of Ordinal Optimization. Readership: Professionals in industrial and systems engineering, graduate reference for probability & statistics, stochastic analysis and general computer science, and research."-- _cProvided by publisher
588	0		_aPrint version record.
504			_aIncludes bibliographical references.
505	0		_aChapter 1. The IPA calculus for hybrid systems -- chapter 2. Smoothed perturbation analysis : a retrospective and prospective look -- chapter 3. Perturbation analysis and variance reduction in Monte Carlo simulation -- chapter 4. Adjoints and averaging -- chapter 5. Infinitesimal perturbation analysis and optimization algorithms -- chapter 6. Simulation-based optimization of failure-prone continuous flow lines -- chapter 7. Perturbation analysis, dynamic programming, and beyond -- chapter 8. Fundamentals of ordinal optimization -- chapter 9. Optimal computing budget allocation framework -- chapter 10. Nested partitions -- chapter 11. Applications of ordinal optimization.
546			_aEnglish.
590			_aAdded to collection customer.56279.3
650		0	_aDiscrete-time systems _xMathematical models. _9599165
650		0	_aPerturbation (Mathematics) _94301
650		0	_aSystems engineering _xComputer simulaton. _9697033
650		6	_aSystèmes échantillonnés _xModèles mathématiques. _91074825
650		6	_aPerturbation (Mathématiques)
650		7	_aSCIENCE _xSystem Theory. _2bisacsh _923421
650		7	_aTECHNOLOGY & ENGINEERING _xOperations Research. _2bisacsh _928722
650		7	_aDiscrete-time systems _xMathematical models _2fast _9599165
650		7	_aPerturbation (Mathematics) _2fast _94301
700	1		_aChen, Chun-Hung, _d1964- _eeditor. _9697034
700	1		_aJia, Qing-Shan, _d1980- _eeditor. _9697035
700	1		_aLee, Loo Hay, _eeditor. _9587515
776	0	8	_iPrint version: _tStochastic simulation optimization for discrete event systems. _d[Hackensack] New Jersey : World Scientific, 2013 _z9789814513005 _w(DLC) 2013012700 _w(OCoLC)842879862
856	4	0	_3EBSCOhost _uhttps://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=605588
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938			_aebrary _bEBRY _nebr10731547
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938			_aCengage Learning _bGVRL _nGVRL8RHC
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994			_a92 _bN$T
999			_c756824 _d756824