We have collection of more than 1 Million open source products ranging from Enterprise product to
small libraries in all platforms. We aggregate information from all open source repositories.
Search and find the best for your needs. Check out projects section.
The Distributed Genetic Programming Framework is a scalable Java genetic programming environment. It comes with an optional specialization for evolving assembler-syntax algorithms. The evolution can be performed in parallel in any computer network.
The following example attempts to minimize the Drop-Wave function which is known to have a minimum value of -1.There is a lot of intellectual fog around the concept of genetic algorithms (GAs). It's important to appreciate the fact that GAs are composed of many nuts and bolts. There isn't a single definition of genetic algorithms. gago is intended to be a toolkit where one may run many kinds of genetic algorithms, with different evolution models and various genetic operators.
The Shared Genomics project has developed parallelised statistical applications (MPI/OpenMP) which can analyse large genomic data-sets containing thousands of Single Nucleotide Polymorphisms (SNP). The code is based on the popular PLINK SNP-analysis program.
Concurrent Programming Library provides an opportunity to develop a parallel programs using .net framework 2.0 and above. It includes an implementation of various parallel algorithms, thread-safe collections and patterns.
FGA (Fast Genetic Algorithm) is a simple yet powerful implementation of genetic algorithms. The library provides many variants of crossover and selection procedures, and a parallel version of the algorithm is included.
Java API for implementing any kind of Genetic Algorithm and Genetic Programming applications quickly and easily. Contains a wide range of ready-to-use GA and GP algorithms and operators to be plugged-in or extended. Includes Tutorials and Examples.