Fuzzy-Like Multiple Objective Multistage Decision Making

1. Front Matter

   Pages 1-23

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2. Multiple Objective Multistage Decision Making

   • Jiuping Xu, Ziqiang Zeng

   Pages 1-68

3. Elements of Fuzzy-Like MOMSDM

   • Jiuping Xu, Ziqiang Zeng

   Pages 69-107

4. Fuzzy MOMSDM for Dynamic Machine Allocation

   • Jiuping Xu, Ziqiang Zeng

   Pages 109-166

5. Fuzzy MOMSDM for Closed Multiclass Queueing Networks

   • Jiuping Xu, Ziqiang Zeng

   Pages 167-197

6. Fuzzy Random MOMSDM for Inventory Management

   • Jiuping Xu, Ziqiang Zeng

   Pages 199-261

7. Fuzzy Random MOMSDM for Facilities Planning

   • Jiuping Xu, Ziqiang Zeng

   Pages 263-320

8. Fuzzy Random MOMSDM for Transportation Assignment

   • Jiuping Xu, Ziqiang Zeng

   Pages 321-347

9. Back Matter

   Pages 349-378

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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

• Computational Intelligence
• Decision Making
• Fuzzy-Like Multiple Objective Multistage Decision Making

• Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu, People's Republic of China

  Jiuping Xu, Ziqiang Zeng

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