Paper Info
Title
A Genetic and Evolutionary Programming Environment with Spatially Structured Populations and Built-In Parallelism
Abstract
The recent development of the Genetic and Evolutionary Computation field lead to a kaleidoscope of approaches to problem solving, which are based on a common background. These shared principles are used in order to develop a programming environment that enhances modularity, in terms of software design and implementation. The system's core encapsulates the main features of the Genetic and Evolutionary Algorithms, by identifying the entities at stake and implementing them as hierarchies of software modules. This architecture is enriched with the parallelization of the algorithms, based on spatially structured populations, following coarse-grained (Island Model) and fine-grained (Neighborhood Model) strategies. A distributed physical implementation, under the PVM environment, running in a local network, is described.
Year
DOI
Venue
2001
10.1007/3-540-45517-5_43
IEA/AIE
Keywords
Field
DocType
common background,pvm environment,physical implementation,island model,built-in parallelism,evolutionary programming,neighborhood model,software module,programming environment,evolutionary computation field lead,software design,spatially structured populations,evolutionary algorithms,evolutionary algorithm,evolutionary computing,genetics
Software design,Evolutionary algorithm,Computer science,Evolutionary computation,Genetic representation,Kaleidoscope,Evolutionary programming,Genetic algorithm,Modularity,Distributed computing
Conference
ISBN
Citations 
PageRank 
3-540-42219-6
0
0.34
References 
Authors
7
4
Name
Order
Citations
PageRank
Miguel Rocha151154.06
Filipe Pereira211.06
Sónia Afonso300.34
José Neves410018.37