Автор: Ignacy Kaliszewski Название: Soft Computing for Complex Multiple Criteria Decision Making ISBN: 1441940189 ISBN-13(EAN): 9781441940186 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book concentrates on providing technical tools to make the user of Multiple Criteria Decision Making (MCDM) methodologies independent of bulky optimization computations. These bulky computations have been a necessary, but limiting, characteristic of interactive MCDM methodologies and algorithms.
Автор: Ching-Lai Hwang; Kwangsun Yoon Название: Multiple Attribute Decision Making ISBN: 3540105581 ISBN-13(EAN): 9783540105589 Издательство: Springer Рейтинг: Цена: 11173.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The literature on methods and applications of Multiple Attribute Decision Making (MADM) has been reviewed and classified systematically. Part IV of the survey deals with the applications of these MADM methods.
Автор: F.P. Hwang; Shu-Jen Chen; Ching-Lai Hwang Название: Fuzzy Multiple Attribute Decision Making ISBN: 3540549986 ISBN-13(EAN): 9783540549987 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this monograph, the literature on methods of fuzzy Multiple Attribute Decision Making (MADM) has been reviewed thoroughly and critically, and classified systematically. The basic concepts and algorithms from the classical MADM methods have been used in the development of the fuzzy MADM methods.
Автор: Huchang Liao; Zeshui Xu Название: Hesitant Fuzzy Decision Making Methodologies and Applications ISBN: 9811032645 ISBN-13(EAN): 9789811032646 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- 1 Hesitant Fuzzy Set and Its Extensions.- 2 Novel Correlation and Entropy Measures for Hesitant Fuzzy Set.- 3 Multiple Criteria Decision Making with Hesitant Fuzzy Hybrid Weighted Aggregation Operators.- 4 Hesitant Fuzzy Multiple Criteria Decision Making with Complete Weight Information.- 5 Hesitant Fuzzy Multiple Criteria Decision Making with Incomplete Weights.- 6 Decision Making with Hesitant Fuzzy Preference Relation.
Автор: G?nter Fandel; T. Hanne; Tomas Gal Название: Multiple Criteria Decision Making ISBN: 3540620974 ISBN-13(EAN): 9783540620976 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume presents recent results in theory, methodology and applications of multiple criteria decision-making (MCDM). All facets of MCDM are included, like fuzzy models, nonlinear convex problems, simulated annealing, integer programming models and goal programming.
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: Young-Jou Lai; Ching-Lai Hwang Название: Fuzzy Multiple Objective Decision Making ISBN: 3540575952 ISBN-13(EAN): 9783540575955 Издательство: Springer Рейтинг: Цена: 20263.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Methods of crisp, fuzzy and possibilistic multiple objective decision-making are systematically reviewed and classified in this volume. The reader is provided with a survey of existing methods and their application to the analysis of fuzzy programming problems.
Автор: Xu Jiuping, Tao Zhimiao Название: Rough Multiple Objective Decision Making ISBN: 143987235X ISBN-13(EAN): 9781439872352 Издательство: Taylor&Francis Рейтинг: Цена: 31390.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory.
Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques--and some that employ simulation-based intelligent algorithms--to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions.
Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research.
Автор: Tzeng, Gwo-Hshiung , Huang, Jih-Jeng Название: Fuzzy Multiple Objective Decision Making ISBN: 0367379643 ISBN-13(EAN): 9780367379643 Издательство: Taylor&Francis Рейтинг: Цена: 9798.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Multi-objective programming (MOP) can simultaneously optimize multi-objectives in mathematical programming models, but the optimization of multi-objectives triggers the issue of Pareto solutions and complicates the derived answers. To address these problems, researchers often incorporate the concepts of fuzzy sets and evolutionary algorithms into MOP models.
Focusing on the methodologies and applications of this field, Fuzzy Multiple Objective Decision Making presents mathematical tools for complex decision making. The first part of the book introduces the most popular methods used to calculate the solution of MOP in the field of multiple objective decision making (MODM). The authors describe multi-objective evolutionary algorithms; expand de novo programming to changeable spaces, such as decision and objective spaces; and cover network data envelopment analysis. The second part focuses on various applications, giving readers a practical, in-depth understanding of MODM.
A follow-up to the authors' Multiple Attribute Decision Making: Methods and Applications, this book guides practitioners in using MODM methods to make effective decisions. It also extends students' knowledge of the methods and provides researchers with the foundation to publish papers in operations research and management science journals.
Автор: Xu Название: Rough Multiple Objective Decision Making ISBN: 1138112712 ISBN-13(EAN): 9781138112711 Издательство: Taylor&Francis Рейтинг: Цена: 12248.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Under intense scrutiny for the last few decades, Multiple Objective Decision Making (MODM) has been useful for dealing with the multiple-criteria decisions and planning problems associated with many important applications in fields including management science, engineering design, and transportation. Rough set theory has also proved to be an effective mathematical tool to counter the vague description of objects in fields such as artificial intelligence, expert systems, civil engineering, medical data analysis, data mining, pattern recognition, and decision theory.
Rough Multiple Objective Decision Making is perhaps the first book to combine state-of-the-art application of rough set theory, rough approximation techniques, and MODM. It illustrates traditional techniques--and some that employ simulation-based intelligent algorithms--to solve a wide range of realistic problems. Application of rough theory can remedy two types of uncertainty (randomness and fuzziness) which present significant drawbacks to existing decision-making methods, so the authors illustrate the use of rough sets to approximate the feasible set, and they explore use of rough intervals to demonstrate relative coefficients and parameters involved in bi-level MODM. The book reviews relevant literature and introduces models for both random and fuzzy rough MODM, applying proposed models and algorithms to problem solutions.
Given the broad range of uses for decision making, the authors offer background and guidance for rough approximation to real-world problems, with case studies that focus on engineering applications, including construction site layout planning, water resource allocation, and resource-constrained project scheduling. The text presents a general framework of rough MODM, including basic theory, models, and algorithms, as well as a proposed methodological system and discussion of future research.
This book describes five qualitative investment decision-making methods based on the hesitant fuzzy information. They are: (1) the investment decision-making method based on the asymmetric hesitant fuzzy sigmoid preference relations, (2) the investment decision-making method based on the hesitant fuzzy trade-off and portfolio selection, (3) the investment decision-making method based on the hesitant fuzzy preference envelopment analysis, (4) the investment decision-making method based on the hesitant fuzzy peer-evaluation and strategy fusion, and (5) the investment decision-making method based on the EHVaR measurement and tail analysis.
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