A Branch-and-Bound Algorithm for Multiobjective Mixed-integer Convex Optimization, Stefan Rockt?schel
Автор: Gilberto Reynoso Meza; Xavier Blasco Ferragud; Jav Название: Controller Tuning with Evolutionary Multiobjective Optimization ISBN: 3319823175 ISBN-13(EAN): 9783319823171 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Поставка под заказ.
Описание: This book is devoted to Multiobjective Optimization Design (MOOD) procedures for controller tuning applications, by means of Evolutionary Multiobjective Optimization (EMO).
Описание: This book highlights a new direction of multiobjective optimization. It introduces sophisticated methods for sequential approximate multiobjective optimization using computational intelligence along with real applications, mainly engineering problems.
Автор: Kaliszewski Ignacy, Miroforidis Janusz, Podkopaev Dmitry Название: Multiple Criteria Decision Making by Multiobjective Optimization: A Toolbox ISBN: 3319813625 ISBN-13(EAN): 9783319813622 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This electroniccompanion contains models of problems to be solved built in Excel spreadsheetfiles.Optimizationmodels are too often oversimplifications of decision problems met in practice.
Автор: Ichiro Nishizaki; Masatoshi Sakawa Название: Fuzzy and Multiobjective Games for Conflict Resolution ISBN: 379082481X ISBN-13(EAN): 9783790824810 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Decision makers in managerial and public organizations often encounter de- cision problems under conflict or competition, because they select strategies independently or by mutual agreement and therefore their payoffs are then affected by the strategies of the other decision makers.
Автор: Henggeler Antunes, Carlos Joao Alves, Maria Climaco, Joao Название: Multiobjective linear and integer programming ISBN: 3319287443 ISBN-13(EAN): 9783319287447 Издательство: Springer Рейтинг: Цена: 10760.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Introducing multiobjective optimization for students in engineering, management, economics and applied mathematics, this book focuses on multiobjective linear programming and multiobjective integer/mixed integer programming. It is accompanied by an interactive software package which enables students to experiment and enhance their technical skills.
Автор: Yann Collette; Patrick Siarry Название: Multiobjective Optimization ISBN: 3642072836 ISBN-13(EAN): 9783642072833 Издательство: Springer Рейтинг: Цена: 12152.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This text offers many multiobjective optimization methods accompanied by analytical examples, and it treats problems not only in engineering but also operations research and management.
Автор: Claus Hillermeier Название: Nonlinear Multiobjective Optimization ISBN: 3034895011 ISBN-13(EAN): 9783034895019 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Arguably, many industrial optimization problems are of the multiobjective type.
Автор: Masatoshi Sakawa; Hitoshi Yano; Ichiro Nishizaki Название: Linear and Multiobjective Programming with Fuzzy Stochastic Extensions ISBN: 1461493986 ISBN-13(EAN): 9781461493983 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This self-contained book offers comprehensive coverage of linear programming, multiobjective programming, fuzzy programming, stochastic programming, and fuzzy stochastic programming, with applications in purchase and transportation planning for food retailing.
Автор: Luc Dinh The Название: Multiobjective Linear Programming: An Introduction ISBN: 3319369776 ISBN-13(EAN): 9783319369778 Издательство: Springer Рейтинг: Цена: 12722.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Three of the most popular methods for solving multiobjective linear problems are explained, and exercises are provided at the end of each chapter, helping students to grasp and apply key concepts and methods to more complex problems.
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.
Автор: Juditsky Anatoli, Nemirovski Arkadi Название: Statistical Inference Via Convex Optimization ISBN: 0691197296 ISBN-13(EAN): 9780691197296 Издательство: Wiley Рейтинг: Цена: 13939.00 р. Наличие на складе: Поставка под заказ.
Описание:
This authoritative book draws on the latest research to explore the interplay of high-dimensional statistics with optimization. Through an accessible analysis of fundamental problems of hypothesis testing and signal recovery, Anatoli Juditsky and Arkadi Nemirovski show how convex optimization theory can be used to devise and analyze near-optimal statistical inferences.
Statistical Inference via Convex Optimization is an essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their optimization methods. Juditsky and Nemirovski provide the first systematic treatment of the statistical techniques that have arisen from advances in the theory of optimization. They focus on four well-known statistical problems--sparse recovery, hypothesis testing, and recovery from indirect observations of both signals and functions of signals--demonstrating how they can be solved more efficiently as convex optimization problems. The emphasis throughout is on achieving the best possible statistical performance. The construction of inference routines and the quantification of their statistical performance are given by efficient computation rather than by analytical derivation typical of more conventional statistical approaches. In addition to being computation-friendly, the methods described in this book enable practitioners to handle numerous situations too difficult for closed analytical form analysis, such as composite hypothesis testing and signal recovery in inverse problems.
Statistical Inference via Convex Optimization features exercises with solutions along with extensive appendixes, making it ideal for use as a graduate text.
Автор: Zaslavski Alexander J. Название: The Projected Subgradient Algorithm in Convex Optimization ISBN: 3030602990 ISBN-13(EAN): 9783030602994 Издательство: Springer Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The discussion takes into consideration the fact that for every algorithm its iteration consists of several steps and that computational errors for different steps are different, in general.
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