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Evokit is an integrated environment for developing evolutionary computation algorithms. It is built around Java and the Eclipse platform, and will support several different libraries including ECJ.
JCLEC is a general purpose evolutionary computation framework developed in Java. Some of its mains features are: multilevel architecture, highly reusable and integrable with other systems, easy to use and a lot of implemented algorithms and operation
Library for optimization using a genetic algorithm or particle swarms
libfgen is a library that implements an efficient and customizable genetic algorithm (GA). It also provides particle swarm optimization (PSO) functionality and an interface for real-valued function minimization or model fitting. It is written in C, but can also be compiled with a C++ compiler. Both Linux and Windows are supported.
A novel and effictive GA algorithm to solve optimization problem
Classical genetic algorithm suffers heavy pressure of fitness evaluation for time-consuming optimization problems. To address this problem, we present an efficient genetic algorithm by the combination with clustering methods. The high efficiency of the proposed method results from the fitness estimation and the schema discovery of partial individuals in current population and.
Specifically, the clustering method used in this paper is affinity propagation. The numerical experiments...
Ky eshte nje projekt i HAPUR/FALAS per publikun Shqip-foles i cili permban nje seri Video-Kursesh, Udhezime, dhe Shembuj Kodi per gjuhe (web) si: XHTML, CSS, JS, PHP, AS3 etj. si dhe per Desktop: C++, Java, Adobe Air etj. + programe/praktika te ndryshme.
This project aims to create an open source genetic algorithms (GA) library for the IBM Cell BE processor. A well-documented implementation of GAs is provided, along with a number of sample fitness functions illustrating how to use the GA library.
unEvo is an Eclipse plug-in that provides support for the experimentation and research process on Evolutionary Algorithms, intended so that the user can implement an evolutionary algorithm without lost time in the code of the algorithm.