Knowledge Incorporation in Evolutionary Computation

This carefully edited book puts together the state-of-the-art and recent advances in knowledge incorporation in evolutionary computation within a unified framework. The book provides a comprehensive self-contained view of knowledge incorporation in evolutionary computation including a concise introd...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Jin, Yaochu (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2005.
Edición:1st ed. 2005.
Colección:Studies in Fuzziness and Soft Computing, 167
Temas:
Mathematics.
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Applications of Mathematics.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • I Introduction
  • A Selected Introduction to Evolutionary Computation
  • II Knowledge Incorporation in Initialization, Recombination and Mutation
  • The Use of Collective Memory in Genetic Programming
  • A Cultural Algorithm for Solving the Job Shop Scheduling Problem
  • Case-Initialized Genetic Algorithms for Knowledge Extraction and Incorporation
  • Using Cultural Algorithms to Evolve Strategies in A Complex Agent-based System
  • Methods for Using Surrogate Models to Speed Up Genetic Algorithm Optimization: Informed Operators and Genetic Engineering
  • Fuzzy Knowledge Incorporation in Crossover and Mutation
  • III Knowledge Incorporation in Selection and Reproduction
  • Learning Probabilistic Models for Enhanced Evolutionary Computation
  • Probabilistic Models for Linkage Learning in Forest Management
  • Performance-Based Computation of Chromosome Lifetimes in Genetic Algorithms
  • Genetic Algorithm and Case-Based Reasoning Applied in Production Scheduling
  • Knowledge-Based Evolutionary Search for Inductive Concept Learning
  • An Evolutionary Algorithm with Tabu Restriction and Heuristic Reasoning for Multiobjective Optimization
  • IV Knowledge Incorporation in Fitness Evaluations
  • Neural Networks for Fitness Approximation in Evolutionary Optimization
  • Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems
  • Model Assisted Evolution Strategies
  • V Knowledge Incorporation through Life-time Learning and Human-Computer Interactions
  • Knowledge Incorporation Through Lifetime Learning
  • Local Search Direction for Multi-Objective Optimization Using Memetic EMO Algorithms
  • Fashion Design Using Interactive Genetic Algorithm with Knowledge-based Encoding
  • Interactive Evolutionary Design
  • VI Preference Incorporation in Multi-objective Evolutionary Computation
  • Integrating User Preferences into Evolutionary Multi-Objective Optimization
  • Human Preferences and their Applications in Evolutionary Multi-Objective Optimization
  • An Interactive Fuzzy Satisficing Method for Multi-objective Integer Programming Problems through Genetic Algorithms
  • Interactive Preference Incorporation in Evolutionary Engineering Design.

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