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Titlebook: Business Optimization Using Mathematical Programming; An Introduction with Josef Kallrath Textbook 2021Latest edition Springer Nature Switz

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期刊全称Business Optimization Using Mathematical Programming
期刊简称An Introduction with
影响因子2023Josef Kallrath
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发行地址Presents a comprehensive introduction into business optimization from a mathematical programming perspective.Includes a large variety of case studies using linear and nonlinear programing, both contin
学科分类International Series in Operations Research & Management Science
图书封面Titlebook: Business Optimization Using Mathematical Programming; An Introduction with Josef Kallrath Textbook 2021Latest edition Springer Nature Switz
影响因子.This 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..
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Modeling Structures Using Mixed Integer Programming,divisible entities (people, living animals, air planes, etc.), and particularly binary variables. Among other things, binary variables can be used to model .In particular, we shall concentrate on the use of binary variables to model simple nonlinear features. Such features can be handled because bin
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How Optimization Is Used in Practice: Case Studies in Integer Programming,blems of increasing size and complexity. The first group of case studies considers a contract allocation problem, metal ingot production, and a project planning problem. This follows a more extensive scheduling problem in the carton industry.
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,Beyond LP and MILP Problems ⊖,herefore, it is not intended to cover these topics in complete depth, but the reader should at least be aware that modeling real-world problems is not restricted to linear models. In fractional programming we show how to transform the problem to linear programming, and successive linear programming
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