Legrand / Liefooghe / Lepagnot | Artificial Evolution | Buch | 978-3-032-07997-8 | www2.sack.de

Buch, Englisch, 240 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 394 g

Reihe: Lecture Notes in Computer Science

Legrand / Liefooghe / Lepagnot

Artificial Evolution

16th International Conference, Évolution Artificielle, EA 2024, Bordeaux, France, October 29-31, 2024, Revised Selected Papers
Erscheinungsjahr 2025
ISBN: 978-3-032-07997-8
Verlag: Springer

16th International Conference, Évolution Artificielle, EA 2024, Bordeaux, France, October 29-31, 2024, Revised Selected Papers

Buch, Englisch, 240 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 394 g

Reihe: Lecture Notes in Computer Science

ISBN: 978-3-032-07997-8
Verlag: Springer


This book constitutes the refereed post-conference proceedings of the 16th International Conference on Artificial Evolution, EA 2024, held in Bordeaux, France, during October 29–31, 2024.

The 16 full papers were carefully reviewed and selected from 30 submissions. The papers cover a wide range of topics in the field of artificial evolution, including Algorithmics and Modeling, Implementations, Application of Evolutionary Paradigms to the Real World industry, biosciences, Machine Learning and hybridization with other soft computing techniques.

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Weitere Infos & Material


.- GRASP-based memetic algorithm for Multi-period technician routing
problem with mandatory assigned tasks and selective tasks.

.- Investigation of Structures for Routing Rules Designed by Genetic
Programming for the Electric Vehicle Routing Problem,.

.- Optimizing Scheduling for Energy Sales in Public Stations: A Revenue
Management Perspective.

.- A study of an ant-based algorithm to model cyclist behavior in
bicycle-friendly cities.

.- Paving the way towards evolutionary machine teaching: an application
to 4-part harmony.

.- Scalable Local Optima Networks for Continuous Search Spaces.

.- Comparing Quantum Annealer and Metaheuristic Methods to Solve the
Steiner Tree Problem.

.- Classi cation vs Regression Models in a Decision Tree-based Interactive
Evolutionary Multi-objective Optimization Algorithm.

.- Tackling Long-Range Dependencies in Dynamic Range Compression
Modeling via Deep Learning.

.- Optimizing Reservoir Computing with Genetic Algorithm for
High-Dimensional SARS-CoV-2 Hospitalization Forecasting: Impacts of
Genetic Algorithm Hyperparameters on Feature Selection and
Reservoir Computing Hyperparameter Tuning.

.- Can Mutations Replace Local Search? Studying the E ect of Repeated
Genetic Programming Operators in the Unrelated Machines
Environment.

.- Optimizing the Viability of interacting systems with Evolutionary
Algorithms.

.- Single-objective constrained optimization for Gene Regulatory
Networks Modeling.

.- Symbolic Regression of Con dence Intervals for Conformal Prediction.

.- A New Step Size Update Strategy for CMA-ES in Multi-objective
Optimisation.

.- UMDA with random a ne maps.



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