This is the result of the study "Leveraging Benchmarking Data for Informed One-Shot Dynamic Algorithm Selection". A One-shot informed dynamic genetic algorithm selection (DAS) is promoted. We present the theoretical performance and experimental results of the DAS on IOHprofiler problems. This Data set consists of 2 parts: 1. The theoretical performance of the DAS policies for 25 pseudo-Boolean problems defined in IOHprofiler (https://iohprofiler.github.io/). The DAS policies are combinations over 80 GAs and 38 switch targets. 2. The experimental result of 100 DAS polices for the IOHprofiler problems and result of the DAS polices selected with constraints for F8. The 100 DAS polices are the best ones of the theoretical performance, and th...
In recent years, several approaches have been developed for genetic algorithms to enhance their perf...
Many algorithms have evolved in the past decade. Genetic analysis and deep learning are two represen...
The performance of an algorithm often critically depends on its parameter configuration. While a var...
This is the result of the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime...
Dynamic Algorithm Configuration (DAC) tackles the question of how to automatically learn policies to...
The growing interest in dynamic optimisation has accelerated the development of genetic algorithms w...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
This thesis presents three new genetic programming (GP) algorithms designed to enhance robustness of...
Abstract. Human-based genetic algorithms (HBGA) use both human evaluation and innovation to optimize...
Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population...
Abstract. Human-based genetic algorithms (HBGA) use both human evaluation and innovation to optimize...
The field of dynamic optimization is related to the applications of nature-inspired al-gorithms [1]....
The development of algorithms solving computationally hard optimisation problems has a long history....
In many real-world scenarios, in contrast to standard benchmark optimization problems, we may face s...
There has been a growing interest in studying evolutionary algorithms in dynamic environments in rec...
In recent years, several approaches have been developed for genetic algorithms to enhance their perf...
Many algorithms have evolved in the past decade. Genetic analysis and deep learning are two represen...
The performance of an algorithm often critically depends on its parameter configuration. While a var...
This is the result of the study "Automated Configuration of Genetic Algorithms by Tuning for Anytime...
Dynamic Algorithm Configuration (DAC) tackles the question of how to automatically learn policies to...
The growing interest in dynamic optimisation has accelerated the development of genetic algorithms w...
In this work a Genetic Algorithm coding and a required genetic operation library has been developed ...
This thesis presents three new genetic programming (GP) algorithms designed to enhance robustness of...
Abstract. Human-based genetic algorithms (HBGA) use both human evaluation and innovation to optimize...
Selection functions enable Evolutionary Algorithms (EAs) to apply selection pressure to a population...
Abstract. Human-based genetic algorithms (HBGA) use both human evaluation and innovation to optimize...
The field of dynamic optimization is related to the applications of nature-inspired al-gorithms [1]....
The development of algorithms solving computationally hard optimisation problems has a long history....
In many real-world scenarios, in contrast to standard benchmark optimization problems, we may face s...
There has been a growing interest in studying evolutionary algorithms in dynamic environments in rec...
In recent years, several approaches have been developed for genetic algorithms to enhance their perf...
Many algorithms have evolved in the past decade. Genetic analysis and deep learning are two represen...
The performance of an algorithm often critically depends on its parameter configuration. While a var...