000			02650cam a2200277 a 4500
001			2787319
005			20200126093751.0
008			810428s1982 nyua b 001 0 eng
010			_a81005777
020			_a0070366969
035			_a(Sirsi) u992
040			_aEG-CaNU _cEG-CaNU _dEG-CaNU
042			_ancode
082	0	0	_a001.434 _2 19
100	1		_aLaw, Averill M. _917619
245	1	0	_aSimulation modeling and analysis / _c Averill M. Law, W. David Kelton.
260			_aNew York : _b McGraw-Hill, _c c1982.
300			_axiv, 400 p. : _b ill. ; _c 24 cm.
490		0	_aMcGraw-Hill series in industrial engineering and management science
504			_aIncludes bibliographies and index.
505	0		_a1. Basic simulation modeling -- 2. Modeling complex systems -- 3. Simulation langauges -- 4. Review of basic probability and statistics -- 5. Selecting input probability distributions -- 6. Random-number generators -- 7. Generating random variables -- 8. Output data analysis for a single system -- 9. Statistical techniques for comparing alternative systems -- 10. Validation of simulation models -- 11. Variance-reduction techniques -- 12. Experimental design and optimization.
520			_aSince the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research.
650		0	_aDigital computer simulation. _917621
700	1		_aKelton, W. David. _9163
596			_a1
999			_c8686 _d8686