Intelligent Evolutionary Optimization
Autor Hua Xu, Yuan Yuanen Limba Engleză Paperback – 22 apr 2024
• Introduces biologically-inspired intelligent optimization algorithms capable of effectively solving complex optimization problems, teaching readers how to apply these algorithms and improve existing optimization techniques
• Explores multi-objective optimization problems in high-dimensional spaces for readers to understand how to perform efficient search and optimization, acquiring strategies and tools adapted to high-dimensional environments
• Presents the practical applications of intelligent evolutionary optimization in various fields to help readers gain insights into the latest trends and application scenarios in the field and receive practical guidance and solutions
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Specificații
ISBN-13: 9780443274008
ISBN-10: 0443274002
Pagini: 386
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0443274002
Pagini: 386
Dimensiuni: 191 x 235 mm
Greutate: 0.45 kg
Editura: ELSEVIER SCIENCE
Cuprins
Part I: Evolutionary Algorithm for Many-Objective Optimization
1. Preliminary
2. A New Dominance Relation Based Evolutionary Algorithm for Many-Objective Optimization
3. Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers
4. Objective Reduction in Many-Objective Optimization: Evolutionary Multi-objective Approach and Critical
5. Expensive Multi-objective Evolutionary Optimization Assisted by Dominance Prediction
Part II: Heuristic Algorithm for Flexible Job Shop Scheduling Problem
6. Preliminary
7. A Hybrid Harmony Search Algorithm for the Flexible Job Shop Scheduling Problem
8. Flexible Job Shop Scheduling Using Hybrid Differential Evolution Algorithms
9. An Integrated Search Heuristic for Large-scale Flexible Job Shop Scheduling Problems
10. Multi-objective Flexible Job Shop Scheduling Using Memetic Algorithms
1. Preliminary
2. A New Dominance Relation Based Evolutionary Algorithm for Many-Objective Optimization
3. Balancing Convergence and Diversity in Decomposition-Based Many-Objective Optimizers
4. Objective Reduction in Many-Objective Optimization: Evolutionary Multi-objective Approach and Critical
5. Expensive Multi-objective Evolutionary Optimization Assisted by Dominance Prediction
Part II: Heuristic Algorithm for Flexible Job Shop Scheduling Problem
6. Preliminary
7. A Hybrid Harmony Search Algorithm for the Flexible Job Shop Scheduling Problem
8. Flexible Job Shop Scheduling Using Hybrid Differential Evolution Algorithms
9. An Integrated Search Heuristic for Large-scale Flexible Job Shop Scheduling Problems
10. Multi-objective Flexible Job Shop Scheduling Using Memetic Algorithms