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008			210831s2021 sz | o |||| 0|eng d
020			_a9783030732370
024	7		_a10.1007/978-3-030-73237-0 _2doi
040			_aES-VaU _bspa _cES-VaU _dES-VaU
050		4	_aT57.6-.97 _b2021 EB
100	1		_aKallrath, Josef. _eautor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	0	0	_aBusiness Optimization Using Mathematical Programming : _bAn Introduction with Case Studies and Solutions in Various Algebraic Modeling Languages _cby Josef Kallrath
250			_a2nd ed. 2021.
264		1	_aCham _c2021 _bSpringer International Publishing
300			_a1 recurso en línea
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
490	0		_aInternational Series in Operations Research & Management Science _x2214-7934 _v307
505	0		_aOptimization: Using Models, Validating Models, Solutions, Answers -- From the Problem to its Mathematical Formulation -- Mathematical Solution Techniques -- Problems Solvable Using Linear Programming -- How Optimization is Used in Practice: Case Studies in Linear Programming -- Modeling Structures Using Mixed Integer Programming -- Types of Mixed Integer Linear Programming Problems -- Case Studies and Problem Formulations -- User Control of the Optimization Process and Improving Efficiency -- How Optimization is Used in Practice: Case Studies in Integer Programming -- Beyond LP and MILP Problems -- Mathematical Solution Techniques - The Nonlinear World -- Global Optimization in Practice -- Polylithic Modeling and Solution Approaches -- Cutting & Packing beyond and within Mathematical Programming -- The Impact and Implications of Optimization -- Concluding Remarks and Outlook.
520			_aThis book presents a structured approach to formulate, model, and solve mathematical optimization problems for a wide range of real world situations. Among the problems covered are production, distribution and supply chain planning, scheduling, vehicle routing, as well as cutting stock, packing, and nesting. The optimization techniques used to solve the problems are primarily linear, mixed-integer linear, nonlinear, and mixed integer nonlinear programming. The book also covers important considerations for solving real-world optimization problems, such as dealing with valid inequalities and symmetry during the modeling phase, but also data interfacing and visualization of results in a more and more digitized world. The broad range of ideas and approaches presented helps the reader to learn how to model a variety of problems from process industry, paper and metals industry, the energy sector, and logistics using mathematical optimization techniques.
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-73237-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Valencia)
942			_2lcc _cLE
988			_aSpringer_Business_2021
999			_c239421 _d239421