Applications of Fuzzy Optimization and Fuzzy Decision Making

doi:10.3390/books978-3-0365-2266-1

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Applications of Fuzzy Optimization and Fuzzy Decision Making

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October 2021

416 pages

ISBN978-3-0365-2265-4 (Hardback)
ISBN978-3-0365-2266-1 (PDF)

https://0-doi-org.brum.beds.ac.uk/10.3390/books978-3-0365-2266-1

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This book is a reprint of the Special Issue Applications of Fuzzy Optimization and Fuzzy Decision Making that was published in

Computer Science & Mathematics

Engineering

Physical Sciences

Public Health & Healthcare

Summary

The aim of the Special Issue “Applications of Fuzzy Optimization and Fuzzy Decision Making” is to expand the applicability of fuzzy optimization and decision making for solving various types of problems in the areas of economics, business, engineering, management, operations research, etc. Any experimental research or empirical study of theoretical developments in fuzzy optimization and decision making is highly welcome. Additionally, research papers presenting solution methods and/or studying their computational complexity, and proposing new algorithms to solve fuzzy optimization and decision making problems, in an effective and efficient manner, are also welcome. We are looking forward to receive innovative approaches that apply, in practical settings, state-of-the art mathematical/algorithmic techniques from fuzzy technology, computational intelligence and soft-computing methodologies, with the aim to offer robust solutions for complex optimization and decision making problems characterized by non-probabilistic uncertainty, vagueness, ambiguity, and hesitation. Such type of papers will address the suitability, validity, and advantages of using fuzzy technologies and the enhancement of them using intelligent methods to treat real-life problems from various disciplines.

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Keywords

fuzzy best worst method; driver behavior factors; road safety; DBQ; Budapest city; complex fuzzy set; similarity measure; complex fuzzy measure; Mamdani Complex Fuzzy Inference System (M-CFIS); rule reduction; granular computing; discrete events system; max–min (fuzzy) algebra; interval matrix; interval eigenvector; fuzzy; manufacturing; modeling; electrical discharge machining (EDM); technological tables; productivity; learning; interval fuzzy number; mixed binary quadratic programming; ordered weighted average; covering-based fractional orthotriple fuzzy rough sets; fractional orthotriple fuzzy β-covering decision-theoretic rough sets; fractional orthotriple fuzzy β-neighborhood; multi-attribute decision making; decision-theoretic rough sets; low-carbon energy (LCE); clean energy technology; policy; multicriteria decision making (MCDM); fuzzy methodologies; SWOT; FGP; SF-AHP; F-TOPSIS; fuzzy analytic hierarchy process; fuzzy geometric mean; alpha-cut operations; piecewise linear; waste segregation; failure mode and effects analysis; intuitionistic fuzzy hybrid weighted Euclidean distance operator; PAPRIKA; type-2 fuzzy inference systems; traffic simulator; traffic accidents; road safety; space perception; speed perception; ridge fuzzy regression; α-level estimation algorithm; fuzzy linear regression; intervention strategy; COVID-19 pandemic; layered partial consensus; fuzzy analytic hierarchy process; cognitive graphs; self organizing maps; tensor distance metrics; higher order data; topological error; Myers-Briggs Type Indicator; MBTI; fuzzy cognitive maps; optimization; forecasting time series; evolutionary algorithms; decision making; appliances energy prediction; electricity distribution; factor elicitation for efficiency; fuzzy analytical hierarchical process (F-AHP); fuzzy models; complex networks; biological networks; neural networks; epidemic models; Acquired Immunodeficiency Syndrome (AIDS); Human Immunodeficiency Virus (HIV); electricity consumption; yield learning; fuzzy forecasting; green manufacturing; law enforcement; case-based reasoning (CBR); similarity measure; hidden property; judgment debtor