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NEW OPTIMIZATION TECHNOLOGY & PLANNING EXPERIMENT. Technology is designed for multidimensional optimization practical problems with continuous object functions. Technology higher efficiency than traditional optimization methods.
JGAP is a Genetic Algorithms and Genetic Programming package written in Java. It is designed to require minimum effort to use, but is also designed to be highly modular. JGAP features grid functionality and a lot of examples. Many unit tests included.
Legal notice/Impressum:
Klaus Meffert
An der Struth 25
D-65510 Idstein
sourceforge <at> klausmeffert.de
Framework for development of simple evolutionary algorithms / island models programs in distributed environment using MapReduce programming model based on hadoop.
X-GAT (XML-based Genetic Algorithm Toolkit) is a Java framework to optimize problems with Genetic Algorithms (GAs). Differently from other frameworks, X-GAT contains ready-to-use GAs implementations and new features can be easily added.
Sleepwalker aims to provide a highly abstract, universal, reusable, extensible Java-based genetic algorithms framework which can be used as a basis for modelling and programming virtually any practical optimisation problem.