TY - CHAP A1 - Eduardo Fernández-González A2 - Inés Vega-López A3 - Jorge Navarro-Castillo ED1 - Shangce Gao Y1 - 2012-03-07 PY - 2012 T1 - Public Portfolio Selection Combining Genetic Algorithms and Mathematical Decision Analysis N2 - Bio-inspired computational algorithms are always hot research topics in artificial intelligence communities. Biology is a bewildering source of inspiration for the design of intelligent artifacts that are capable of efficient and autonomous operation in unknown and changing environments. It is difficult to resist the fascination of creating artifacts that display elements of lifelike intelligence, thus needing techniques for control, optimization, prediction, security, design, and so on. Bio-Inspired Computational Algorithms and Their Applications is a compendium that addresses this need. It integrates contrasting techniques of genetic algorithms, artificial immune systems, particle swarm optimization, and hybrid models to solve many real-world problems. The works presented in this book give insights into the creation of innovative improvements over algorithm performance, potential applications on various practical tasks, and combination of different techniques. The book provides a reference to researchers, practitioners, and students in both artificial intelligence and engineering communities, forming a foundation for the development of the field. BT - Bio-Inspired Computational Algorithms and Their Applications SP - Ch. 8 UR - https://doi.org/10.5772/38121 DO - 10.5772/38121 SN - PB - IntechOpen CY - Rijeka Y2 - 2020-08-07 ER -