We present evidence indicating that adding a crossover island greatly improves the performance of a Dynamic Island Model for Adaptive Operator Selection. Two combinatorial optimisation problems are considered: the Onemax benchmark, to prove the concept; and a real-world formulation of the course timetabling problem to test practical relevance. Crossover is added to the recently proposed dynamic island adaptive model for operator selection which considered mutation only. When comparing the models with and without a recombination, we found that having a crossover island significantly improves the performance. Our experiments also provide compelling evidence of the dynamic role of crossover during search: it is a useful operator across the who...
International audienceSeveral techniques have been proposed to tackle the Adaptive Operator Selectio...
The goal of adaptive operator selection is the on-line control of the choice of variation operators ...
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level ...
International audienceWe present evidence indicating that adding a crossover island greatly improves...
In this paper we propose a generic framework for Dynamic Island Models, which can be used as an orig...
The purpose of adaptive operator selection is to choose dynamically the most suitable variation oper...
Selection is a core genetic operator in many evolutionary algorithms (EAs). The performance of EAs o...
In this paper, we investigate how adaptive operator selection techniques are able to efficiently man...
Adaptive evolutionary algorithms have been widely developed to improve the management of the balance...
There are many different forms of recombination operators available in literature. However, it is di...
In this paper we proposed the use of a dynamic island model which aim at adapting parameter settings...
One of the settings that most affect the performance of Evolutionary Algorithms is the selection of ...
Probability Matching is one of the most successful methods for adaptive operator selection (AOS), th...
. It has long been recognised that the choice of recombination and mutation operators and the rates ...
One of the issues in evolutionary algorithms (EAs) is the relative importance of two search operator...
International audienceSeveral techniques have been proposed to tackle the Adaptive Operator Selectio...
The goal of adaptive operator selection is the on-line control of the choice of variation operators ...
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level ...
International audienceWe present evidence indicating that adding a crossover island greatly improves...
In this paper we propose a generic framework for Dynamic Island Models, which can be used as an orig...
The purpose of adaptive operator selection is to choose dynamically the most suitable variation oper...
Selection is a core genetic operator in many evolutionary algorithms (EAs). The performance of EAs o...
In this paper, we investigate how adaptive operator selection techniques are able to efficiently man...
Adaptive evolutionary algorithms have been widely developed to improve the management of the balance...
There are many different forms of recombination operators available in literature. However, it is di...
In this paper we proposed the use of a dynamic island model which aim at adapting parameter settings...
One of the settings that most affect the performance of Evolutionary Algorithms is the selection of ...
Probability Matching is one of the most successful methods for adaptive operator selection (AOS), th...
. It has long been recognised that the choice of recombination and mutation operators and the rates ...
One of the issues in evolutionary algorithms (EAs) is the relative importance of two search operator...
International audienceSeveral techniques have been proposed to tackle the Adaptive Operator Selectio...
The goal of adaptive operator selection is the on-line control of the choice of variation operators ...
Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level ...