Soft Computing Based Optimization and Decision Models

Soft Computing Based Optimization and Decision Models: To Commemorate the 65th Birthday of Professor José Luis “Curro” Verdegay (Studies in Fuzziness and Soft Computing)

This book offers a timely snapshot of current soft-computing research and solutions to decision-making and optimization problems, which are ubiquitous in the current social and technological context, addressing fields including logistics, transportation and data analysis.  Written by leading international experts from the United States, Brazil and Cuba, as well as the United Kingdom, France, Finland and Spain, it discusses theoretical developments in and practical applications of soft computing in fields where these methods are crucial to obtaining better models, including: intelligent transportation systems, maritime logistics, portfolio selection, decision- making, fuzzy cognitive maps, and fault detection.  The book is dedicated to Professor José L. Verdegay, a pioneer who has been actively pursuing research in fuzzy sets theory and soft computing since 1982, in honor of his 65th birthday.

Table of Contents

Chapter 1. A Review of Soft Computing Techniques in Maritime Logistics and Its Related Fields
Chapter 2. Intelligent Data Analysis, Soft Computing and Imperfect Data
Chapter 3. Soft Computing Methods in Transport and Logistics
Chapter 4. Applications of Soft Computing in Intelligent Transportation Systems
Chapter 5. Fuzzy Cognitive Maps Based Models for Pattern Classification: Advances and Challenges
Chapter 6. A Proposal of On-Line Detection of New Faults and Automatic Learning in Fault Diagnosis
Chapter 7. Fuzzy Portfolio Selection Models for Dealing with Investor’s Preferences
Chapter 8. On Fuzzy Convex Optimization to Portfolio Selection Problem
Chapter 9. 9 Digital Coaching for Real Options Support
Chapter 10. 10 An Analysis of Decision Criteria for the Selection of Military Training Aircrafts
Chapter 11. Participatory Search in Evolutionary Fuzzy Modeling
Chapter 12. 12 But, What Is It Actually a Fuzzy Set?
Chapter 13. Gradual Numbers and Fuzzy Solutions to Fuzzy Optimization Problems
Chapter 14. 14 Using Fuzzy Measures to Construct Multi-criteria Decision Functions
Chapter 15. A Modal Account of Preference in a Fuzzy Setting
Chapter 16. On Possibilistic Dependencies: A Short Survey of Recent Developments
Chapter 17. Penalty Function in Optimization Problems: A Review of Recent Developments
Chapter 18. The Single Parameter Family of Gini Bonferroni Welfare Functions and the Binomial Decomposition, Transfer Sensitivity and Positional Transfer Sensitivity