Title
Evolutionary Multiobjective System Design: Theory And Applications (Chapman & Hall/Crc Computer And Information Science Series),New
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Realworld Engineering Problems Often Require Concurrent Optimization Of Several Design Objectives, Which Are Conflicting In Cases. This Type Of Optimization Is Generally Called Multiobjective Or Multicriterion Optimization. The Area Of Research That Applies Evolutionary Methodologies To Multiobjective Optimization Is Of Special And Growing Interest. It Brings A Viable Computational Solution To Many Realworld Problems.Generally, Multiobjective Engineering Problems Do Not Have A Straightforward Optimal Design. These Kinds Of Problems Usually Inspire Several Solutions Of Equal Efficiency, Which Achieve Different Tradeoffs. Decision Makers Preferences Are Normally Used To Select The Most Adequate Design. Such Preferences May Be Dictated Before Or After The Optimization Takes Place. They May Also Be Introduced Interactively At Different Levels Of The Optimization Process. Multiobjective Optimization Methods Can Be Subdivided Into Classical And Evolutionary. The Classical Methods Usually Aim At A Single Solution While The Evolutionary Methods Provide A Whole Set Of Socalled Paretooptimal Solutions.Evolutionary Multiobjective System Design: Theory And Applicationsprovides A Representation Of The Stateoftheart In Evolutionary Multiobjective Optimization Research Area And Related New Trends. It Reports Many Innovative Designs Yielded By The Application Of Such Optimization Methods. It Also Presents The Application Of Multiobjective Optimization To The Following Problems:Embrittlement Of Stainless Steel Coated Electrodeslearning Fuzzy Rules From Imbalanced Datasetscombining Multiobjective Evolutionary Algorithms With Collective Intelligencefuzzy Gain Scheduling Controlsmart Placement Of Roadside Units In Vehicular Networkscombining Multiobjective Evolutionary Algorithms With Quasisimplex Local Searchdesign Of Robust Substitution Boxesprotein Structure Prediction Problemcore Assignment For Efficient Networkonchipbased System Design
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- Q: What is the main focus of the book 'Evolutionary Multi-Objective System Design: Theory and Applications'? A: The book focuses on multi-objective optimization in engineering, particularly how evolutionary methodologies can address real-world problems involving conflicting design objectives.
- Q: Who is the author of the book? A: The author of the book is Nadia Nedjah.
- Q: What topics are covered in this book? A: The book covers various applications of multi-objective optimization including embrittlement of stainless steel, learning fuzzy rules from imbalanced datasets, and protein structure prediction.
- Q: What is the significance of multi-objective optimization? A: Multi-objective optimization is significant because it allows for the identification of multiple efficient solutions that balance trade-offs among conflicting objectives, which is crucial in engineering design.
- Q: What type of binding does this book have? A: This book is available in paperback binding.
- Q: How many pages does 'Evolutionary Multi-Objective System Design' contain? A: The book contains 218 pages.
- Q: When was this book published? A: The book was published on June 30, 2020.
- Q: Is this book suitable for beginners in multi-objective optimization? A: While the book provides valuable insights into advanced topics, it is more suitable for readers with some background in optimization methods, as it delves into complex applications and theories.
- Q: What series is this book part of? A: This book is part of the Chapman & Hall/CRC Computer and Information Science Series.
- Q: What edition of the book is available? A: The book is available in its first edition.