"This book explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications"--
The meta-heuristic hybrid optimization techniques discussed in this collection address the intrinsic difficulty of algorithms and the need to model uncertainty problems troubling modern industrial, business, and financial systems. Mexican and Iranian contributors describe algorithms for inventory and supply chain management problems, compare Lagrangian relaxations of a two stage facility location problem, and propose an ANN self-tuning frequency control design for an isolated microgrid. Other topics of the 20 papers include particle swarm for optimal power flow, the relationship between stock returns and earnings, robot motion control, generator maintenance scheduling, and weighted affinity measure clustering for online data mining. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com)