Date du colloque : 12/2010International audienceThis work presents a dynamic island model framework for helping the resolution of combinatorial optimization problems with evolutionary algorithms. In this framework, the possible migrations among islands are represented by a complete graph. The migrations probabilities associated to each edge are dynamically updated with respect to the last migrations impact. This new framework is tested on the well-known 0/1 Knapsack problem and MAX-SAT problem. Good results are obtained and several properties of this framework are studied.</p
Abstract:- Almost all real-world problems are dynamic and as such not all problem instances are know...
[[abstract]]In this paper, the effects of adapting the migration intervals on the performance and so...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of c...
Abstract. This work presents a dynamic island model framework for helping the resolution of combinat...
Abstract. This work presents a dynamic island model framework for helping the resolution of combinat...
International audienceIn this paper, we recall the dynamic island model concept, in order to dynamic...
Date du colloque : 07/2012International audienceIn this paper we propose a generic framework fo...
International audienceIn this paper we proposed the use of a dynamic island model which aim at adapt...
International audienceDynamic island models are population-based algorithms for solving optimization...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters o...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters o...
In evolutionary computation approaches such as genetic programming (GP), preventing premature conver...
Parallel Genetic Algorithms have often been reported to yield better performance than Genetic Algori...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computa...
Abstract:- Almost all real-world problems are dynamic and as such not all problem instances are know...
[[abstract]]In this paper, the effects of adapting the migration intervals on the performance and so...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of c...
Abstract. This work presents a dynamic island model framework for helping the resolution of combinat...
Abstract. This work presents a dynamic island model framework for helping the resolution of combinat...
International audienceIn this paper, we recall the dynamic island model concept, in order to dynamic...
Date du colloque : 07/2012International audienceIn this paper we propose a generic framework fo...
International audienceIn this paper we proposed the use of a dynamic island model which aim at adapt...
International audienceDynamic island models are population-based algorithms for solving optimization...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters o...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters...
In this paper, we propose a self Adaptive Migration Model for Genetic Algorithms, where parameters o...
In evolutionary computation approaches such as genetic programming (GP), preventing premature conver...
Parallel Genetic Algorithms have often been reported to yield better performance than Genetic Algori...
This book provides a compilation on the state-of-the-art and recent advances of evolutionary computa...
Abstract:- Almost all real-world problems are dynamic and as such not all problem instances are know...
[[abstract]]In this paper, the effects of adapting the migration intervals on the performance and so...
Recently, it has been proven that evolutionary algorithms produce good results for a wide range of c...