Parallel Problem Solving from Nature - PPSN XVIII
18th International Conference, PPSN 2024, Hagenberg, Austria, September 14-18, 2024, Proceedings, Part IV
Herausgegeben: Affenzeller, Michael; Winkler, Stephan M.; Kononova, Anna V.; Trautmann, Heike; Tusar, Tea; Machado, Penousal; Bäck, Thomas
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This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Co...
This multi-volume LNCS set, LNCS 15148-15151, constitutes the refereed proceedings of the 18th International Conference on Parallel Problem Solving from Nature, PPSN 2024, held in Hagenberg, Austria, in September 2024.
The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:
Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.
Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.
Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.
Part IV: Multi-Objective Optimization; Real-World Applications.
The 101 full papers presented in these proceedings were carefully reviewed and selected from 294 submissions. The papers presented in these four volumes are organized in the following topical sections:
Part I: Combinatorial Optimization; Genetic Programming; Fitness Landscape Modeling and Analysis.
Part II: Benchmarking and Performance Measures; Automated Algorithm Selection and Configuration; Numerical Optimization; Bayesian- and Surrogate-Assisted Optimization.
Part III: Theoretical Aspects of Nature-Inspired Optimization; (Evolutionary) Machine Learning and Neuroevolution; Evolvable Hardware and Evolutionary Robotics.
Part IV: Multi-Objective Optimization; Real-World Applications.
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