Difference between revisions of "Evoptool: Evolutionary Optimization Tool"
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== '''Project profile''' == | == '''Project profile''' == | ||
| + | {| style="color:black; background-color:#F9F9F9;" cellpadding="10" cellspacing="0" border="1" | ||
| + | |- | ||
| + | ||'''Name:''' | ||
| + | ||evoptool: Evolutive Optimization Tool. | ||
| + | |- | ||
| + | ||'''Field:''' | ||
| + | ||Combining Estimation of Distribution Algorithms and other Evolutionary techniques | ||
| + | for combinatorial optimization. | ||
| + | |- | ||
| + | ||'''Project's head:''' | ||
| + | ||M. Matteucci - [[User:MatteoMatteucci]] | ||
| + | L. Malagò - [[User:LuigiMalago]] | ||
| + | |- | ||
| + | ||'''People involved:''' | ||
| + | ||G. Valentini - [[User:GabrieleValentini]] | ||
| + | |} | ||
| − | === | + | === Short description === |
| − | + | The project focus on the study, implementation, comparison and analysis of different algorithms for combinatorial optimization using techniques and algorithms proposed in Evolutionary Computation. In particular we are interested in the study of Estimation of Distribution Algorithms, a recent meta-heuristic, often presented as an evolution of Genetic Algorithms, where classical crossover and mutation operators, used in genetic algorithms, are replaced with operators that come from statistics, such as sampling and estimation. | |
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| − | The project | + | |
The focus will be on the implementation of new hybrid algorithms able to combine estimation of distribution algorithms with different approaches available in the evolutionary computation literature, such as genetic algorithms and evolutionary strategies, together with other local search techniques. | The focus will be on the implementation of new hybrid algorithms able to combine estimation of distribution algorithms with different approaches available in the evolutionary computation literature, such as genetic algorithms and evolutionary strategies, together with other local search techniques. | ||
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== '''User Manual''' == | == '''User Manual''' == | ||
Revision as of 20:58, 26 May 2009
Project profile
| Name: | evoptool: Evolutive Optimization Tool. |
| Field: | Combining Estimation of Distribution Algorithms and other Evolutionary techniques
for combinatorial optimization. |
| Project's head: | M. Matteucci - User:MatteoMatteucci
L. Malagò - User:LuigiMalago |
| People involved: | G. Valentini - User:GabrieleValentini |
Short description
The project focus on the study, implementation, comparison and analysis of different algorithms for combinatorial optimization using techniques and algorithms proposed in Evolutionary Computation. In particular we are interested in the study of Estimation of Distribution Algorithms, a recent meta-heuristic, often presented as an evolution of Genetic Algorithms, where classical crossover and mutation operators, used in genetic algorithms, are replaced with operators that come from statistics, such as sampling and estimation. The focus will be on the implementation of new hybrid algorithms able to combine estimation of distribution algorithms with different approaches available in the evolutionary computation literature, such as genetic algorithms and evolutionary strategies, together with other local search techniques.
User Manual
Algorthms
In this tool there are several bla bla bla..
- GA
- GB
Objective Functions
Graphic User Interface
Command Line
Documentation
Evoptool is a software with the purpose to compare the performance of several different algorithms from the Evolutive family and, for obvious reasons, with some algorithms from the classical Operation Research family. Evoptool is written in C++ for the GNU/Linux platform and it exploit the Gtk libraries (in this case gtkmm libraries) and GNUplot utility. Inside this tool there are several implemented algorithms and some wrapped ones from already existing applications.
Software Modules
Evoptool is made up of several different modules (or libraries). This architecture make easy to organize files and better understanding how the application work.
- common - It contains commons classes and ancestors for the algorithm modules and for the optimization function module.
- ga - It contains the implementation of several Genetic Algorithms.
- eda - It contains the implementation of several Estimation Distribution Algorithms.
- geda - It contains the implementation of several gEDAs.
- or - It contains the implementation of some algorithms from the classical Operation Research.
- opt-pbl - It contains the implementation of several objective functions (fitness), that represents different problem instances.
- gui - This module is the main one, it contains all the classes for manage GUI (algorithm decorators). From the other side it implements the multithread mechanism under the GUI, and last but not list it contains the wrapped applications and take care about wrapping.
- misc - It contains general utility classes such rondom seed geerator.
- shared -
Hierarchies
Algorithms Hierarchy
Decorators Hierarchy
Objective Functions Hierarchy
Usefull Links
- Evoptool Repository (Need authentication!)
- GNU Scientific Library
- GUI Library Gtkmm
- Boost Library
- Gnuplot Utility
- C++ Library reference
