To successfully search multiple coadaptive subcomponents in a solution, we developed a novel cooperative evolutionary algorithm based on a new computational multilevel selection framework. This algorithm constructs cooperative solutions hierarchically by implementing the idea of group selection. We show that this simple and straightforward algorithm is able to accelerate evolutionary speed and improve solution accuracy on string covering problems as compared to other EAs used in literature. In addition, the structure of the solution and the roles played by each subcomponent in the solution emerge as a result of evolution without human in-terference
The identification, design, and implementation of strategies for cooperation is a central research i...
Abstract—The intuitive idea that good solutions to small problems can be reassembled into good solut...
Combining depth with evolutionary algorithms, a deep evolutionary algorithm, the group competition c...
This paper aims to improve the capability of genetic pro-gramming to tackle the evolution of coopera...
In many complex practical optimization cases, the dominant characteristics of the problem are often ...
. Cooperative search is a parallelization strategy for search algorithms where parallelism is obtai...
Cooperative co-evolution algorithms (CCEA) are a thriving sub-field of evolutionary computation. Thi...
To debunk the myth of how cooperation can emerge through the competition induced by Evolutionary Com...
Standard Cooperative Co-evolution uses a round-robin method to select subcomponents to undergo optim...
the date of receipt and acceptance should be inserted later Abstract Cooperative co-evolution algori...
Cooperative coevolutionary algorithms decompose a problem into several subcomponents and optimize th...
The Multi-Level Selection Genetic Algorithm (MLSGA) is shown to increase the performance of a simple...
This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partn...
IEEE The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong in 19...
We propose a multilevel cooperative search algorithm to compute upper bounds for Cλ(v,k,t), the mini...
The identification, design, and implementation of strategies for cooperation is a central research i...
Abstract—The intuitive idea that good solutions to small problems can be reassembled into good solut...
Combining depth with evolutionary algorithms, a deep evolutionary algorithm, the group competition c...
This paper aims to improve the capability of genetic pro-gramming to tackle the evolution of coopera...
In many complex practical optimization cases, the dominant characteristics of the problem are often ...
. Cooperative search is a parallelization strategy for search algorithms where parallelism is obtai...
Cooperative co-evolution algorithms (CCEA) are a thriving sub-field of evolutionary computation. Thi...
To debunk the myth of how cooperation can emerge through the competition induced by Evolutionary Com...
Standard Cooperative Co-evolution uses a round-robin method to select subcomponents to undergo optim...
the date of receipt and acceptance should be inserted later Abstract Cooperative co-evolution algori...
Cooperative coevolutionary algorithms decompose a problem into several subcomponents and optimize th...
The Multi-Level Selection Genetic Algorithm (MLSGA) is shown to increase the performance of a simple...
This paper examines the use of a hierarchical coevolutionary genetic algorithm under different partn...
IEEE The first cooperative co-evolutionary algorithm (CCEA) was proposed by Potter and De Jong in 19...
We propose a multilevel cooperative search algorithm to compute upper bounds for Cλ(v,k,t), the mini...
The identification, design, and implementation of strategies for cooperation is a central research i...
Abstract—The intuitive idea that good solutions to small problems can be reassembled into good solut...
Combining depth with evolutionary algorithms, a deep evolutionary algorithm, the group competition c...