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008			220601s2021 sz | s |||| 0|eng d
020			_a9783031024931
024	7		_a10.1007/978-3-031-02493-1 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTS155 _b2021 EB
100	1		_aDaskin, Mark S., _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687597 _d1952-
245	1	0	_aBite-Sized Operations Management _cby Mark S. Daskin
250			_a1st edition 2021
264		1	_aCham _bSpringer International Publishing _c2021
300			_a1 recurso en línea (XXIII, 169 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Operations Research and Applications _x2770-6311
505	0		_aList of Figures -- List of Tables -- Preface -- Acknowledgments -- Introduction to Operations Management -- Fundamentals of Uncertainty Analysis -- Intuition About Probability -- Discrete Probability Distributions -- Continuous Probability Distributions -- Functions of a Random Variable -- Fundamentals of Optimization -- Basic Inventory Management -- Inventory Management with Uncertain Demand -- Introduction to Linear Programming -- The Transportation Problem -- Assigning Students to Seminars -- Analytic Location Modeling -- Minimizing the Average Distance to a Facility -- A Facility Location Tradeoff -- Fundamentals of Queueing Theory -- A Single-Server Queue -- A More General Single-Server Queue and The Impact of Variability on Queueing Performance -- A Simple Multi-Server Queue -- Solving Queueing Equations Numerically and Simulating the Performance of a Queue -- Decision Theory -- Summary, Where to Next, and Final Thoughts -- Index -- Author's Biography.
520			_aThis text is an introduction to Operations Management. Three themes are woven throughout the book: optimization or trying to do the best we can, managing tradeoffs between conflicting objectives, and dealing with uncertainty. After a brief introduction, the text reviews the fundamentals of probability including commonly used discrete and continuous distributions and functions of a random variable. The next major section, beginning in Chapter 7, examines optimization. The key fundamentals of optimization-inputs, decision variables, objective(s), and constraints-are introduced. Optimization is applied to linear regression, basic inventory modeling, and the newsvendor problem, which incorporates uncertain demand. Linear programming is then introduced. We show that the newsvendor problem can be cast as a network flow linear programming problem. Linear programming is then applied to the problem of redistributing empty rental vehicles (e.g., bicycles) at the end of a day and the problem of assigning students to seminars. Several chapters deal with location models as examples of both simple optimization problems and integer programming problems. The next major section focuses on queueing theory including single-and multi-server queues. This section also introduces a numerical method for solving for key performance metrics for a common class of queueing problems as well as simulation modeling. Finally, the text ends with a discussion of decision theory that again integrates notions of optimization, tradeoffs, and uncertainty analysis. The text is designed for anyone with a modest mathematical background. As such, it should be readily accessible to engineering students, economics, statistics, and mathematics majors, as well as many business students.
988			_aSynthesis Collection of Technology_2021
650		7	_2embne _9145705 _aOptimización matemática
650		7	_2embne _9150644 _aGestión de la producción _xModelos matemáticos
650		7	_2embne _9138098 _aIndustria _xModelos matemáticos
776	0	8	_iPrinted edition: _z9783031003219
776	0	8	_iPrinted edition: _z9783031013652
776	0	8	_iPrinted edition: _z9783031036217
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02493-1 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI