Multistage Decision-making Under Fuzziness PDF Download

Author: Janusz Kacprzyk
Publisher:
ISBN:
Category : Decision making
Languages : en
Pages : 154

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Author: Jiuping Xu
Publisher: Springer
ISBN: 3319033980
Category : Technology & Engineering
Languages : en
Pages : 398

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Book Description
Decision has inspired reflection of many thinkers since the ancient times. With the rapid development of science and society, appropriate dynamic decision making has been playing an increasingly important role in many areas of human activity including engineering, management, economy and others. In most real-world problems, decision makers usually have to make decisions sequentially at different points in time and space, at different levels for a component or a system, while facing multiple and conflicting objectives and a hybrid uncertain environment where fuzziness and randomness co-exist in a decision making process. This leads to the development of fuzzy-like multiple objective multistage decision making. This book provides a thorough understanding of the concepts of dynamic optimization from a modern perspective and presents the state-of-the-art methodology for modeling, analyzing and solving the most typical multiple objective multistage decision making practical application problems under fuzzy-like uncertainty, including the dynamic machine allocation, closed multiclass queueing networks optimization, inventory management, facilities planning and transportation assignment. A number of real-world engineering case studies are used to illustrate in detail the methodology. With its emphasis on problem-solving and applications, this book is ideal for researchers, practitioners, engineers, graduate students and upper-level undergraduates in applied mathematics, management science, operations research, information system, civil engineering, building construction and transportation optimization

Author: Richard Bellman
Publisher:
ISBN:
Category : Fuzzy sets
Languages : en
Pages : 76

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Author: Janusz Kacprzyk
Publisher: Wiley-Blackwell
ISBN: 9780470744161
Category : Fuzzy systems
Languages : en
Pages : 424

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Book Description
This valuable and timely publication from a highly acclaimed expert in the field provides an overall view of the discipline of multistage fuzzy control as well as a wealth of new ideas in decision-making and reinforcement learning Multistage Fuzzy Control 2nd Edition follows its predecessor, a classic in the field, in explaining the essential principles of fuzzy logic and describing both the theoretical and practical advantages of a model-based, prescriptive approach. In the 10 years since the first edition however, a myriad of new perspectives and developments have emerged - many as a result of the author s own research that earned him the 2006 IEEE Computational Intelligence Society Fuzzy Systems Pioneer Award for pioneering works on multistage fuzzy control. The use of some fuzzy tools for the analysis and optimization of multistage decision-making and control, notably of a fuzzy dynamic programming type, is now considered important and popular with researchers from different fields. This new edition features 30% new material in both theory and applications, with much space devoted to new research into reinforcement learning (a sub-area of machine learning concerned with how actions are to be taken in an environment so as to maximize some long term reward), and also to some extensions towards fuzzy reinforcement learning or neurofuzzy reinforcement learning. It also includes many new elements related to IT (information technology), notably to data mining, learning, bioinformatics, etc. Multistage Fuzzy Control 2nd Edition is an essential handbook for those wishing to resolve real-world problems in control and decision analysis through the use of fuzzy-logic-based methods. Offers a valuable and timely publication from a highly acclaimed expert in the field, providing an overall view of the discipline of multistage fuzzy control as well as a wealth of new research. Presents 30% new material, including important new ideas such as reinforcement learning, neurofuzzy architectures, evolutionary optimization and applications in the areas of bioinformatics, mobile robots and computer communication. Includes a range of new applications related to power engineering, such as the use of fuzzy dynamic programming for water reservoir control, mobile robot control, data transfer control in computer networks, sequential pattern mining and predicting the secondary structure of ribonucleic acid (and some other problems in bioinformatics.

Author: Yuji Yoshida
Publisher: Physica
ISBN: 3790818178
Category : Business & Economics
Languages : en
Pages : 246

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Book Description
The concept of fuzziness, inspired by Zadeh (1965), brings us fruitful results when it is applied to problems in decision making. Recently, problems in fuzzy decision making are getting more complex, and one of the most complex fac tors is dynamics in systems. Dynamical approach to fuzzy decision making has been proposed by Bellman and Zadeh's celebrated paper "Decision-making in a fuzzy environment" (1970). The idea has developed into fuzzy mathemati cal programming and has been applied in many fields including management science, operations research, control theory, engineering, systems analysis, computer science, mathematical finance etc. Dynamic programming, advo cated in Bellmans book "Dynamic programming" (1957), is one of the most powerful tools to deal with dynamics in systems, and Bellman and Zadeh has proposed the optimality principle in fuzzy decision making by (1970) introducing fuzzy dynamic programming. Fuzzy dynamic programming and fuzzy mathematical programming has been making remakable progress after they were given life by Bellman and Zadeh's paper (1970). In this volume, various kinds of dynamics, not only time but also structure of systems, are considered. This volume contains ten reviewed papers, which deal with dynamics in theory and applications and whose topics are poten tially related to dynamics and are expected to develope dynamical study in near future. first, fuzzy dynamic programming is reviewed from a viewpoint of its origin and consider its developement in theory and applications.

Author: Guangquan Zhang
Publisher: Springer
ISBN: 3662460599
Category : Technology & Engineering
Languages : en
Pages : 385

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Book Description
This monograph presents new developments in multi-level decision-making theory, technique and method in both modeling and solution issues. It especially presents how a decision support system can support managers in reaching a solution to a multi-level decision problem in practice. This monograph combines decision theories, methods, algorithms and applications effectively. It discusses in detail the models and solution algorithms of each issue of bi-level and tri-level decision-making, such as multi-leaders, multi-followers, multi-objectives, rule-set-based, and fuzzy parameters. Potential readers include organizational managers and practicing professionals, who can use the methods and software provided to solve their real decision problems; PhD students and researchers in the areas of bi-level and multi-level decision-making and decision support systems; students at an advanced undergraduate, master’s level in information systems, business administration, or the application of computer science.

Author: E. Stanley Lee
Publisher: Springer Science & Business Media
ISBN: 1447106830
Category : Technology & Engineering
Languages : en
Pages : 199

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Book Description
Managerial Decisions in hierarchy organizations, such as the various manufacturing and service companies, are difficult to formalize and even more difficult to optimize. By exploring the typical fuzziness, vagueness, or the "not-well-defined" nature of such organizations, this book presents the first comprehensive treatment of this difficult and practically important problem. The advantages of the proposed fuzzy interactive approach are that it significantly reduces computational requirements. Equally, the representation of the system is made more realistic through the recognition of the inherent fuzziness of such large organizations. Both the multi-ploy and the game-like decision making processes, also known as multi-level programming and the fuzzy interactive approach, are discussed in detail. The emphasis is on numerical algorithms and numerous examples are solved and compared. The concepts of fuzzy set and fuzzy linguistic representation, which form an integral part of any managerial decision, are also discussed.

Author: Roman Slowiński
Publisher: Springer Science & Business Media
ISBN: 1461556457
Category : Mathematics
Languages : en
Pages : 467

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Book Description
Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory. It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to reliability analysis. These topics are covered within four parts: Decision Making, Mathematical Programming, Statistics and Data Analysis, and Reliability, Maintenance and Replacement. The scope and content of the book has resulted from multiple interactions between the editor of the volume, the series editors, the series advisory board, and experts in each chapter area. Each chapter was written by a well-known researcher on the topic and reviewed by other experts in the area. These expert reviewers sometimes became co-authors because of the extent of their contribution to the chapter. As a result, twenty-five authors from twelve countries and four continents were involved in the creation of the 13 chapters, which enhances the international character of the project and gives an idea of how carefully the Handbook has been developed.

Author: Chi-Bin Cheng
Publisher: Springer
ISBN: 3319925253
Category : Technology & Engineering
Languages : en
Pages : 225

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Book Description
This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.

Author: Hans-Jürgen Zimmermann
Publisher: Springer Science & Business Media
ISBN: 9400932499
Category : Business & Economics
Languages : en
Pages : 342

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Book Description
In the two decades since its inception by L. Zadeh, the theory of fuzzy sets has matured into a wide-ranging collection of concepts, models, and tech niques for dealing with complex phenomena which do not lend themselves to analysis by classical methods based on probability theory and bivalent logic. Nevertheless, a question which is frequently raised by the skeptics is: Are there, in fact, any significant problem areas in which the use of the theory of fuzzy sets leads to results which could not be obtained by classical methods? The approximately 5000 publications in this area, which are scattered over many areas such as artificial intelligence, computer science, control engineering, decision making, logic, operations research, pattern recognition, robotics and others, provide an affirmative answer to this question. In spite of the large number of publications, good and comprehensive textbooks which could facilitate the access of newcomers to this area and support teaching were missing until recently. To help to close this gap and to provide a textbook for courses in fuzzy set theory which can also be used as an introduction to this field, the first volume ofthis book was published in 1985 [Zimmermann 1985 b]. This volume tried to cover fuzzy set theory and its applications as extensively as possible. Applications could, therefore, only be described to a limited extent and not very detailed.