Evolutionary Algorithms in Java (JavaEvA)
JavaEvA is a framework for Evolutionary and general Optimising
Algorithms implemented in Java. It is developed as resumption of
the former Evolutionary Algorithms (EvA)
software package. Using the Java mechanism of Remote Method Invocation
(RMI) the algorithms of JavaEvA can be distributed via Intra- or
Internet. Thus, it is possible to handle complex optimisation problems.
JavaEvA as a client server application is divided into two parts:
a swing-based graphical user interface (EvAClient) and the optimization
kernel (EvAServer) which contains the different optimization algorithms.
JavaEvA includes Evolutionary Algorithms (EA) like Genetic Algorithms
(GA), Evolutionary Strategies (ES), Population Based Incremental
Learning (PBIL) and many more. Besides, model-based Optimisation
Techniques like methods from the research field of Design of Experiment,
Efficient Global Optimisation (EGO) and Model-Assisted Evolution
Strategies (MAES) are implemented in JavaEvA. Concerning model-based
Optimisation Techniques, several mathematical models can be used
like Gaussian Processes, Support Vector Machines, Radial-Basis-Function
networks etc.. A comprehensive library of neural network implementations
is available, using the JavaNNS
JavaEvA was developed as part of the BMBF-Project called "Automated
Crystallization". JavaEvA will be used here to optimise parameters
for an automated production process for crystalline catalysts that
yield the highest production output and the best catalytic properties
of the produced crystals.
JavaEvA has been applied as teaching aid in lecture tutorials,
on several optimisation problems within our research group and as
developing platform in student research projects.
Holger Ulmer, Tel.: (07071) 29 70441
Felix Streichert, Tel.: (07071) 29 70436
Last changes: 19.03.2018, 18:46 CET.
© 2001-2004 University of Tübingen