Fuzzy Decision Making Methods Based On Prospect Theory And Its Application In Venture Capital
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Fuzzy Decision-Making Methods Based on Prospect Theory and Its Application in Venture Capital
This book gives a thorough and systematic introduction to the latest research results about fuzzy decision-making method based on prospect theory. It includes eight chapters: Introduction, Intuitionistic fuzzy MADM based on prospect theory, QUALIFLEX based on prospect theory with probabilistic linguistic information, Group PROMETHEE based on prospect theory with hesitant fuzzy linguistic information, Prospect consensus with probabilistic hesitant fuzzy preference information, Improved TODIM based on prospect theory and the improved TODIM with probabilistic hesitant fuzzy information, etc. This book is suitable for the researchers in the fields of fuzzy mathematics, operations research, behavioral science, management science and engineering, etc. It is also useful as a textbook for postgraduate and senior-year undergraduate students of the relevant professional institutions of higher learning.
A Method of Determining Multi-AttributeWeights Based on Single-Valued Neutrosophic Numbers and Its Application in TODIM
In this paper, the TODIM method is used to solve the multi-attribute decision-making problem with unknown attribute weight in venture capital, and the decision information is given in the form of single-valued neutrosophic numbers. In order to consider the objectivity and subjectivity of decision-making problems reasonably, the optimal weight is obtained by combining subjective weights and objective weights. Subjective weights are given directly by decision makers. Objective weights are obtained by establishing a weight optimization model with known decision information, then this method will compare with entropy weight method. These simulation results also validate the effectiveness and reasonableness of this proposed method.
Probabilistic Linguistic Two-Sided Matching Decision-Making Methods and Applications
This book tackles the intricacies of decision-making processes where alternatives stem from distinct, finite sets. Discover the cutting-edge in decision-making with our groundbreaking book on complex two-sided matching methods. Harnessing the power of probabilistic linguistic term sets, it introduces innovative methods that enhance matching efficiency and practicality. It addresses the pressing question of how to navigate and optimize in scenarios with multifaceted matching challenges, offering an exploration into the psychological perceptions of agents through consistency checks and pairwise comparisons. It delves into the unknowns of static matching with multiple attribute weights, extends its scope to multi-sided agent sets in complex matching, and introduces dynamic screening mechanisms to refine the matching process. This book is not just a theoretical exploration. It lays the groundwork for intelligent matching algorithms and group mechanisms, providing actionable insights for technical supply and demand allocation, emergency personnel dispatch, and multi-stage medical management scheme selection. The effectiveness of these methods is backed by comparative analyses and simulation experiments, proving their superiority in real-world applications. Embrace the future of decision-making with our book, a must-read for those seeking to master complex matching scenarios and unlock practical solutions.