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Supply Chain Disruption Management: Using Stochastic Mixed Integer Programming, Sawik Tadeusz


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Автор: Sawik Tadeusz
Название:  Supply Chain Disruption Management: Using Stochastic Mixed Integer Programming
ISBN: 9783030448165
Издательство: Springer
Классификация:



ISBN-10: 3030448169
Обложка/Формат: Paperback
Страницы: 467
Вес: 0.70 кг.
Дата издания: 30.05.2021
Язык: English
Размер: 23.39 x 15.60 x 2.57 cm
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains.


50 Years of Integer Programming 1958-2008

Название: 50 Years of Integer Programming 1958-2008
ISBN: 3540682740 ISBN-13(EAN): 9783540682745
Издательство: Springer
Цена: 18167.00 р.
Наличие на складе: Поставка под заказ.

Описание:

In 1958, Ralph E. Gomory transformed the field of integer programming when he published a short paper that described his cutting-plane algorithm for pure integer programs and announced that the method could be refined to give a finite algorithm for integer programming. In January of 2008, to commemorate the anniversary of Gomory's seminal paper, a special session celebrating fifty years of integer programming was held in Aussois, France, as part of the 12th Combinatorial Optimization Workshop. This book is based on the material presented during this session.

50 Years of Integer Programming offers an account of featured talks at the 2008 Aussois workshop, namely

- Michele Conforti, Gerard Cornuejols, and Giacomo Zambelli: Polyhedral Approaches to Mixed Integer Linear Programming

- William Cook: 50+ Years of Combinatorial Integer Programming

- Francois Vanderbeck and Laurence A. Wolsey: Reformulation and Decomposition of Integer Programs

The book contains reprints of key historical articles together with new introductions and historical perspectives by the authors: Egon Balas, Michel Balinski, Jack Edmonds, Ralph E. Gomory, Arthur M. Geoffrion, Alan J. Hoffman & Joseph B. Kruskal, Richard M. Karp, Harold W. Kuhn, and Ailsa H. Land & Alison G. Doig.

It also contains written versions of survey lectures on six of the hottest topics in the field by distinguished members of the integer programming community:

- Friedrich Eisenbrand: Integer Programming and Algorithmic Geometry of Numbers

- Raymond Hemmecke, Matthias Koppe, Jon Lee, and Robert Weismantel: Nonlinear Integer Programming

- Andrea Lodi: Mixed Integer Programming Computation

- Francois Margot: Symmetry in Integer Linear Programming

- Franz Rendl: Semidefinite Relaxations for Integer Programming

- Jean-Philippe P. Richard and Santanu S. Dey: The Group-Theoretic Approach to Mixed Integer Programming

Integer programming holds great promise for the future, and continues to build on its foundations. Indeed, Gomory's finite cutting-plane method for the pure integer case is currently being reexamined and is showing new promise as a practical computational method. This book is a uniquely useful celebration of the past, present and future of this important and active field. Ideal for students and researchers in mathematics, computer science and operations research, it exposes mathematical optimization, in particular integer programming and combinatorial optimization, to a broad audience.

Network Interdiction and Stochastic Integer Programming

Автор: David L. Woodruff
Название: Network Interdiction and Stochastic Integer Programming
ISBN: 1475778236 ISBN-13(EAN): 9781475778236
Издательство: Springer
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Цена: 6986.00 р.
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Описание: On March 15, 2002 we held a workshop on network interdiction and the more general problem of stochastic mixed integer programming at the University of California, Davis. The book is organized with interdiction papers first and the stochastic programming papers in the second part.

Supply Chain Disruption Management: Using Stochastic Mixed Integer Programming

Автор: Sawik Tadeusz
Название: Supply Chain Disruption Management: Using Stochastic Mixed Integer Programming
ISBN: 3030448134 ISBN-13(EAN): 9783030448134
Издательство: Springer
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Цена: 15372.00 р.
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Описание: This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains.

Supply Chain Disruption Management Using Stochastic Mixed Integer Programming

Автор: Tadeusz Sawik
Название: Supply Chain Disruption Management Using Stochastic Mixed Integer Programming
ISBN: 3319864831 ISBN-13(EAN): 9783319864839
Издательство: Springer
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Цена: 13974.00 р.
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Описание:

This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address risk-neutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on innovative, computationally efficient portfolio approaches to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc.

Numerous computational examples throughout the book, modeled in part on real-world supply chain disruption management problems, illustrate the material presented and provide managerial insights. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management.

After an introductory chapter, the book is then divided into five main parts.  Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply (and demand) portfolios and scheduling; and Part V addresses disruption management of information flows in supply chains.
Theory of linear and integer programming

Автор: Schrijver, Alexander
Название: Theory of linear and integer programming
ISBN: 0471982326 ISBN-13(EAN): 9780471982326
Издательство: Wiley
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Цена: 13773.00 р.
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Описание: Theory of Linear and Integer Programming Alexander Schrijver Centrum voor Wiskunde en Informatica, Amsterdam, The Netherlands This book describes the theory of linear and integer programming and surveys the algorithms for linear and integer programming problems, focusing on complexity analysis.

Integer programming

Автор: Wolsey, Laurence A. (universite Catholique De Louv
Название: Integer programming
ISBN: 0471283665 ISBN-13(EAN): 9780471283669
Издательство: Wiley
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Цена: 15602.00 р.
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Описание: This volume is aimed at users of integer programming who wish to understand why some problems are difficult to solve, how techniques can be reformulated to give better results, and how mixed integer programming systems can be used more effectively.

Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course

Автор: Dan Gusfield
Название: Integer Linear Programming in Computational and Systems Biology: An Entry-Level Text and Course
ISBN: 1108421768 ISBN-13(EAN): 9781108421768
Издательство: Cambridge Academ
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Цена: 9029.00 р.
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Описание: Integer linear programming is a versatile modeling and optimization technique with potential to transform biological computation. This hands-on text, designed for students, researchers, and professionals in both biology and computational fields, demonstrates applications in genomics, RNA and protein folding, DNA sequencing, phylogenetics, and more.

Risk Management in Stochastic Integer Programming

Автор: Frederike Neise
Название: Risk Management in Stochastic Integer Programming
ISBN: 3834805475 ISBN-13(EAN): 9783834805478
Издательство: Springer
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Цена: 9781.00 р.
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Описание: I am deeply grateful to my advisor Prof. Dr. Rudiger Schultz for his untiring - couragement. Moreover, I would like to express my gratitude to Prof. Dr. -Ing. - mund Handschin and Dr. -Ing. Hendrik Neumann from the University of Dortmund for inspiration and support. I would like to thank PD Dr. Rene Henrion from the Weierstrass Institute for Applied Analysis and Stochastics in Berlin for reviewing this thesis. Cordial thanks to my colleagues at the University of Duisburg-Essen for motivating and fruitful discussions as well as a pleasurable cooperation. Contents 1 Introduction 1 1. 1 Stochastic Optimization. . . . . . . . . . . . . . . . . . . . . . . 3 1. 1. 1 The two-stage stochastic optimization problem . . . . . . 3 1. 1. 2 Expectation-based formulation. . . . . . . . . . . . . . . 5 1. 2 Content and Structure. . . . . . . . . . . . . . . . . . . . . . . . 6 2 RiskMeasuresinTwo-StageStochasticPrograms 9 2. 1 Risk Measures. . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2. 1. 1 Deviation measures. . . . . . . . . . . . . . . . . . . . . 10 2. 1. 2 Quantile-based risk measures . . . . . . . . . . . . . . . 11 2. 2 Mean-Risk Models . . . . . . . . . . . . . . . . . . . . . . . . . 12 2. 2. 1 Results concerning structure and stability . . . . . . . . . 13 2. 2. 2 Deterministic equivalents. . . . . . . . . . . . . . . . . . 22 2. 2. 3 Algorithmic issues - dual decomposition method . . . . . 26 3 StochasticDominanceConstraints 33 3. 1 Introduction to Stochastic Dominance . . . . . . . . . . . . . . . 33 3. 1. 1 Stochastic orders for the preference of higher outcomes . . 34 3. 1. 2 Stochastic orders for the preference of smaller outcomes . 38 3. 2 Stochastic Dominance Constraints . . . . . . . . . . . . . . . . . 42 3. 2. 1 First order stochastic dominance constraints. . . . . . . . 43 3. 2. 2 Results concerning structure and stability . . . . . . . . . 44 3. 2. 3 Deterministic equivalents. . . . . . . . . . . . . . . . . . 51 3. 2. 4 Algorithmic issues . . . . . . . . . . . . . . . . . . . . .

Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming

Автор: Uwe Gotzes
Название: Decision Making with Dominance Constraints in Two-Stage Stochastic Integer Programming
ISBN: 3834808431 ISBN-13(EAN): 9783834808431
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Uwe Gotzes analyzes an approach to account for risk aversion in two-stage models based upon partial orders on the set of real random variables. He illustrates the superiority of the proposed decomposition method over standard solvers for example with numerical experiments with instances from energy investment.

Operations-Focused Optimized Theater Weather Sensing Strategies Using Preemptive Binary Integer Programming

Автор: Geyer Andrew J.
Название: Operations-Focused Optimized Theater Weather Sensing Strategies Using Preemptive Binary Integer Programming
ISBN: 1249599741 ISBN-13(EAN): 9781249599746
Издательство: Неизвестно
Рейтинг:
Цена: 10658.00 р.
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Production planning by mixed integer programming

Автор: Pochet, Yves Wolsey, Laurence A.
Название: Production planning by mixed integer programming
ISBN: 144192132X ISBN-13(EAN): 9781441921321
Издательство: Springer
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Цена: 8384.00 р.
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Описание: This book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation results, and an easy to use problem-solving library. This approach is demonstrated through a series of real life case studies, exercises and detailed illustrations.

Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

Автор: Mohit Tawarmalani; Nikolaos V. Sahinidis
Название: Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming
ISBN: 1441952357 ISBN-13(EAN): 9781441952356
Издательство: Springer
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Цена: 32142.00 р.
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Описание: Interest in constrained optimization originated with the simple linear pro- gramming model since it was practical and perhaps the only computationally tractable model at the time.


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