Applications of Evolutionary Computation

.- Applications of Evolutionary Computation
.- CP-MEME: A Hybrid (1+1)-Evolutionary Framework for the Oven Scheduling Problem.
.- Multi-Constrained Evolutionary Molecular Design Framework: An Interpretable Drug Design Method Combining Rule-Based Evolution and Molecular Crossover.
.- EvoTADASHI: Genetic Programming for High-Performance Code Optimization.
.- Feasibility-Preserving Multi-Objective Evolutionary Algorithms with Local Search for the Bi-Objective Maximal Covering Location Problem with Compactness.
.- Unconventional Hexacopters via Evolution and Learning: Performance Gains and New Insights.
.- Evolutionary Design of Specialized Image Compression Operators.
.- Adaptive Curriculum Learning in Genetic Programming–Guided Local Search for Large-Scale Vehicle Routing Problems.
.- A Reinforcement Learning–Inspired Latent Yield-based Adaptive Algorithm Switching Mechanism.
.- Domain-Informed Representation for Evolutionary Sieving in Integral and Module Lattices.
.- Evolutionary Emergence of Distributed Neural Network Controllers in Voxel-Based Soft Robots.
.- Evolving Ternary Patterns and Discriminative Localisation for Basal Cell Carcinoma Detection.
.- On the Impact of Conditional Distribution in Discovered Differential Equation Ensembles.
.- From Cooperation to Hierarchy: A Study of Dynamics of Hierarchy Emergence in a Multi-Agent System.
.- On Counts and Densities of Homogeneous Bent Functions: An Evolutionary Approach.
.- Assessing Evolving and Learning-Based Controllers for Efficient Cursor Control in Human–Computer Interaction.
.- A Quantum-Inspired Genetic Algorithm for Multi-Objective Job-Shop Scheduling.
.- Enhancing Genetic Algorithms with Graph Neural Networks: A Timetabling Case Study.
.- Hybrid Modeling for Predicting the Evolution of Premalignant Cervical Squamous Lesions via Intelligent Agents and Deep Neural Networks.
.- Optimizing Transformers: Metaheuristics for Head Attention Pruning.
.- Evolving Memory-Aware Schedules for Transformer Inference on Systolic Array Accelerators.
.- EuroGP & EvoApps Special Joint Track on Evolutionary Machine
.- Generalisation of Automated Algorithm Selection in Black-Box Optimisation: The Role of Algorithm Portfolio and Learning Model.
.- Quality-Diversity Optimization Meets Neuron-centric Hebbian Learning.
.- Multi-Objective Evolutionary Optimization of Imbalanced Fast Feedforward Networks.
.- Toward Reliable Uncertainty Quantification in Surrogate-Assisted Evolutionary Algorithms via Temporal Conformal Prediction.
.- On Efficient Binarization of Scanned Historical Documents by Training Local Rules of Neural Cellular Automata.
.- PITL-DE: Problem-Independent Transfer Learning in Differential Evolution for Continuous Optimization.
.- Exploring the Impact of Fairness-Aware Criteria in AutoML.
.- Learning to Search: A Reinforcement Learning Agent for Global Optimization.
.- TensorRankNEAT: Fast Preference Learning with Neuroevolution using Tensorization and GPUs.
.- Multi-Objective Evolutionary Neural Architecture Search for Hailo Accelerators.
.- Multi-Objective Optimization for Synthetic-to-Real Style Transfer.
.- Biologically-Inspired Homeostasis for Neuroevolution: Alternating Growth and Pruning Phases.
.- Bioinspired Algorithms for Green Computing and Sustainable Complex Systems
.- Self-Organized Criticality for Green Distributed Computing: A Sandpile-Inspired Model of Energy-Efficient Load Balancing.

• Erscheinungsdatum: 08.05.2026
• Autor/Autorin: Pablo García-Sánchez
• Format: E-Book
• Dateiformat: PDF
• Kopierschutz: Wasserzeichen
• Dateigröße: 56.2 MB
• Verlag: SPRINGER
• Sprache: Englisch
• Umfang: 554 Seiten
• ISBN: 9783032236043
• Lieferung: Sofort per Download
• Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
• Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.