Evolutionary Computation in Dynamic and Uncertain Environments

This book provides a compilation on the state-of-the-art and recent advances of evolutionary algorithms in dynamic and uncertain environments within a unified framework. The motivation for this book arises from the fact that some degree of uncertainty in characterizing any realistic engineering syst...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Yang, Shengxiang (Επιμελητής έκδοσης), Ong, Yew-Soon (Επιμελητής έκδοσης), Jin, Yaochu (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2007.
Σειρά:Studies in Computational Intelligence, 51
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Optimum Tracking in Dynamic Environments
  • Explicit Memory Schemes for Evolutionary Algorithms in Dynamic Environments
  • Particle Swarm Optimization in Dynamic Environments
  • Evolution Strategies in Dynamic Environments
  • Orthogonal Dynamic Hill Climbing Algorithm: ODHC
  • Genetic Algorithms with Self-Organizing Behaviour in Dynamic Environments
  • Learning and Anticipation in Online Dynamic Optimization
  • Evolutionary Online Data Mining: An Investigation in a Dynamic Environment
  • Adaptive Business Intelligence: Three Case Studies
  • Evolutionary Algorithms for Combinatorial Problems in the Uncertain Environment of the Wireless Sensor Networks
  • Approximation of Fitness Functions
  • Individual-based Management of Meta-models for Evolutionary Optimization with Application to Three-Dimensional Blade Optimization
  • Evolutionary Shape Optimization Using Gaussian Processes
  • A Study of Techniques to Improve the Efficiency of a Multi-Objective Particle Swarm Optimizer
  • An Evolutionary Multi-objective Adaptive Meta-modeling Procedure Using Artificial Neural Networks
  • Surrogate Model-Based Optimization Framework: A Case Study in Aerospace Design
  • Handling Noisy Fitness Functions
  • Hierarchical Evolutionary Algorithms and Noise Compensation via Adaptation
  • Evolving Multi Rover Systems in Dynamic and Noisy Environments
  • A Memetic Algorithm Using a Trust-Region Derivative-Free Optimization with Quadratic Modelling for Optimization of Expensive and Noisy Black-box Functions
  • Genetic Algorithm to Optimize Fitness Function with Sampling Error and its Application to Financial Optimization Problem
  • Search for Robust Solutions
  • Single/Multi-objective Inverse Robust Evolutionary Design Methodology in the Presence of Uncertainty
  • Evolving the Tradeoffs between Pareto-Optimality and Robustness in Multi-Objective Evolutionary Algorithms
  • Evolutionary Robust Design of Analog Filters Using Genetic Programming
  • Robust Salting Route Optimization Using Evolutionary Algorithms
  • An Evolutionary Approach For Robust Layout Synthesis of MEMS
  • A Hybrid Approach Based on Evolutionary Strategies and Interval Arithmetic to Perform Robust Designs
  • An Evolutionary Approach for Assessing the Degree of Robustness of Solutions to Multi-Objective Models
  • Deterministic Robust Optimal Design Based on Standard Crowding Genetic Algorithm.