Fuzzy-Like Multiple Objective Multistage Decision Making [electronic resource] / by Jiuping Xu, Ziqiang Zeng.

By:

Xu, Jiuping [author.]

Contributor(s):

Material type: Text

TextSeries: Studies in Computational Intelligence ; 533Publisher: Cham : Springer International Publishing : Imprint: Springer, 2014Description: XXIV, 378 p. 111 illus. online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9783319033983

Subject(s):

Additional physical formats: Printed edition:: No titleDDC classification:

006.3 23

LOC classification:

Q342

Online resources:

Click here to access online

Contents:

Multiple Objective Multistage Decision Making -- Elements of Fuzzy-Like MOMSDM -- Fuzzy MOMSDM for Dynamic Machine Allocation -- Fuzzy MOMSDM for Closed Multiclass Queuing Networks -- Fuzzy Random MOMSDM for Inventory Management -- Fuzzy Random MOMSDM for Facilities Planning -- Fuzzy Random MOMSDM for Transportation Assignment.

In: Springer eBooksSummary: 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

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Holdings
Item type	Current library	Call number	Status	Date due	Barcode
E-Book	Central Library		Available		E-41355

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

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