Multi-Objective Memetic Algorithms

The application of sophisticated evolutionary computing approaches for solving complex problems with multiple conflicting objectives in science and engineering have increased steadily in the recent years. Within this growing trend, Memetic algorithms are, perhaps, one of the most successful stories,...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Goh, Chi-Keong (Editor ), Ong, Yew-Soon (Editor ), Tan, Kay Chen (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
Edición:1st ed. 2009.
Colección:Studies in Computational Intelligence, 171
Temas:
Engineering mathematics.
Engineering-Data processing.
Artificial intelligence.
Mathematical and Computational Engineering Applications.
Artificial Intelligence.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Evolutionary Multi-Multi-Objective Optimization - EMMOO
  • Implementation of Multiobjective Memetic Algorithms for Combinatorial Optimization Problems: A Knapsack Problem Case Study
  • Knowledge Infused in Design of Problem-Specific Operators
  • Solving Time-Tabling Problems Using Evolutionary Algorithms and Heuristics Search
  • An Efficient Genetic Algorithm with Uniform Crossover for the Multi-Objective Airport Gate Assignment Problem
  • Application of Evolutionary Algorithms for Solving Multi-Objective Simulation Optimization Problems
  • Feature Selection Using Single/Multi-Objective Memetic Frameworks
  • Multi-Objective Robust Optimization Assisted by Response Surface Approximation and Visual Data-Mining
  • Multiobjective Metamodel-Assisted Memetic Algorithms
  • A Convergence Acceleration Technique for Multiobjective Optimisation
  • Knowledge Propagation through Cultural Evolution
  • Risk and Cost Tradeoff in Economic Dispatch Including Wind Power Penetration Based on Multi-Objective Memetic Particle Swarm Optimization
  • Hybrid Behavioral-Based Multiobjective Space Trajectory Optimization
  • Nature-Inspired Particle Mechanics Algorithm for Multi-Objective Optimization
  • Information Exploited for Local Improvement
  • Combination of Genetic Algorithms and Evolution Strategies with Self-adaptive Switching
  • Comparison between MOEA/D and NSGA-II on the Multi-Objective Travelling Salesman Problem
  • Integrating Cross-Dominance Adaptation in Multi-Objective Memetic Algorithms
  • A Memetic Algorithm for Dynamic Multiobjective Optimization
  • A Memetic Coevolutionary Multi-Objective Differential Evolution Algorithm
  • Multiobjective Memetic Algorithm and Its Application in Robust Airfoil Shape Optimization.

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