Fuzzy Multiple Objective Decision Making

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A01=Gwo-Hshiung Tzeng
A01=Jih-Jeng Huang
advanced multi-objective optimization techniques
Alliance Costs
Author_Gwo-Hshiung Tzeng
Author_Jih-Jeng Huang
Bi-level Programming
Bi-level Programming Problem
Category=PBT
Category=PBW
CCR Efficiency
CCR Efficiency Score
Competence Set
De Novo Programming
decision analysis
EBITDA Margin
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
function
Fuzzy DEA
Fuzzy Mop
Fuzzy Multi-objective Programming
Fuzzy Number
Fuzzy Sets
Genetic Algorithms
graduate level textbook
mathematical
Mellin Transformation
membership
Membership Function
Mop
Mop Problem
Network DEA Model
number
operations research
optimal
Optimal Resource Allocation
pareto
Pareto Solutions
programming
Regression Model
resource allocation methods
set
solution
solutions
strategic alliance modeling
supply chain optimization
Transaction Cost
Transaction Cost Theory
Vice Versa

Product details

  • ISBN 9780367379643
  • Weight: 453g
  • Dimensions: 156 x 234mm
  • Publication Date: 07 Oct 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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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.

Gwo-Hshiung Tzeng is a Distinguished Chair Professor at Kainan University. He is editor-in-chief of the International Journal of Operations Research and the International Journal of Information Systems for Logistics and Management. He received a PhD in management science from Osaka University. His research interests include statistics, multivariate analysis, networks, routing and scheduling, multiple criteria decision making, fuzzy theory, hierarchical structure analysis for application to technology management, energy, environment, transportation systems, transportation investment, logistics, location, urban planning, tourism, technology management, electronic commerce, and global supply chains.

Jih-Jeng Huang is an assistant professor of computer science and information management at Soochow University, where he teaches research methods, multivariate analysis, and capital asset and pricing models. He received a PhD in information management from the National Taiwan University. His research interests include multiple criteria decision making, knowledge management, behavioral economics and finance, and data analysis. His work has been widely published in journals and conference proceedings.

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