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010   $a9786613143860
010   $a981-4282-65-0
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100   $a20110202d2011      uy             0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aStochastic simulation optimization$b[electronic resource] $ean optimal computing budget allocation /$fChun-Hung Chen, Loo Hay Lee
210   $aSingapore ;$aHackensack, N.J. $cWorld Scientific$dc2011
215   $a1 online resource (248 p.)
225 1 $aSystem engineering and operations research ;$vv. 1
300   $aDescription based upon print version of record.
311   $a981-4282-64-2 
320   $aIncludes bibliographical references (p. 219-224) and index.
327   $aForeword; Preface; Acknowledgments; Contents; 1. Introduction to Stochastic Simulation Optimization; 2. Computing Budget Allocation; 3. Selecting the Best from a Set of Alternative Designs; 4. Numerical Implementation and Experiments; 5. Selecting An Optimal Subset; 6. Multi-objective Optimal Computing Budget Allocation; 7. Large-Scale Simulation and Optimization; 8. Generalized OCBA Framework and Other Related Methods; Appendix A: Fundamentals of Simulation; Appendix B: Basic Probability and Statistics; Appendix C: Some Proofs in Chapter 6; Appendix D: Some OCBA Source Codes; References
327   $aIndex
330   $aWith the advance of new computing technology, simulation is becoming very popular for designing large, complex, and stochastic engineering systems, since closed-form analytical solutions generally do not exist for such problems. However, the added flexibility of simulation often creates models that are computationally intractable. Moreover, to obtain a sound statistical estimate at a specified level of confidence, a large number of simulation runs (or replications) is usually required for each design alternative. If the number of design alternatives is large, the total simulation cost can be v
410  0$aSystem engineering and operations research ;$vv. 1.
606   $aSystems engineering$xSimulation methods
606   $aStochastic processes
606   $aMathematical optimization
608   $aElectronic books.
615  0$aSystems engineering$xSimulation methods.
615  0$aStochastic processes.
615  0$aMathematical optimization.
676   $a519.2
700   $aChen$b Chun-hung$0976207
701   $aLee$b Loo Hay$0889759
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910456224003321
996   $aStochastic simulation optimization$92223753
997   $aUNINA