- Evolving Objects (EO): an Evolutionary Computation Framework
+Evolving Objects (EO): an Evolutionary Computation Framework
EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast.
@@ -171,403 +170,399 @@If you need immediate support or have any question, the best way to get answers is to subscribe to the mailing list and send your email to eodev-main@lists.sourceforge.net
- +Alternatively, you can join us on the official chatroom. You can try our webchat interface, or if you already use IRC, you can directly connect to the irc.freenode.org/#paradiseo multi-user chatroom with your favorite client.
- - + + --> + --
- +
+
+ -
Features ⤒
+Features ⤒
-Component-based framework
+Component-based framework
-Designing an algorithm with EO consists in choosing what components you want to use for your specific needs, just as building a structure with Lego blocks.
-If you have a classical problem for which available code exists (for example if you have a black-box problem with real-valued variables), you will just choose components to form an algorithm and connect it to your fitness function (which computes the quality of a given solution).
-If your problem is a bit more exotic, you will have to code a class that represents how your individuals (a solution to your problem) are represented, and perhaps some variations operators, but most of the other operators (selection, replacement, stopping criteria, command-line interface, etc.) are already available in EO.
-
Designing an algorithm with EO consists in choosing what components you want to use for your specific needs, just as building a structure with Lego blocks.
+If you have a classical problem for which available code exists (for example if you have a black-box problem with real-valued variables), you will just choose components to form an algorithm and connect it to your fitness function (which computes the quality of a given solution).
+If your problem is a bit more exotic, you will have to code a class that represents how your individuals (a solution to your problem) are represented, and perhaps some variations operators, but most of the other operators (selection, replacement, stopping criteria, command-line interface, etc.) are already available in EO.
+
Main Features
+Main Features
- + -
- 
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- 
- |
- 
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+ |
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+ |
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-
-
- Flexible design that permits to easily create virtually any algorithm -
- Solution representation for continuous and combinatorial problems:
-
-
-
- binary-strings, -
- permutations, -
- vectors, -
- easily write your own, -
- … -
- - Several algorithm paradigms:
-
-
-
- evolution strategies, -
- genetic algorithms, -
- estimation of distribution, -
- particle swarm optimization -
- … -
- - Many selection and replacement operators:
-
-
-
- rank-based, -
- deterministic or stochastic tournaments, -
- roulette, -
- elitism, -
- … -
- - Ready-to-use variations operators:
-
-
-
- uniform initializer, -
- gaussian mutation, -
- subtree crossover, -
- … -
- - Easy combination of several operators:
-
-
-
- proportional combination, -
- sequential call, -
- … -
- - Parallelization tools
- Shared memory loops unrolling (with OpenMP) -
- Message passing parallelization (with openMPI) +
- Flexible design that permits to easily create virtually any algorithm +
- Solution representation for continuous and combinatorial problems:
-
-
- map/reduce-like design, with operators choice, as in EO
- -
- useful existing operators (parallel dynamic multi-start, static evaluations, …) +
- binary-strings, +
- permutations, +
- vectors, +
- easily write your own, +
- …
+ - Several algorithm paradigms:
+
-
+
- evolution strategies, +
- genetic algorithms, +
- estimation of distribution, +
- particle swarm optimization +
- … +
+ - Many selection and replacement operators:
+
-
+
- rank-based, +
- deterministic or stochastic tournaments, +
- roulette, +
- elitism, +
- … +
+ - Ready-to-use variations operators:
+
-
+
- uniform initializer, +
- gaussian mutation, +
- subtree crossover, +
- … +
+ - Easy combination of several operators:
+
-
+
- proportional combination, +
- sequential call, +
- … +
+ - Parallelization tools +
- Shared memory loops unrolling (with OpenMP) +
- Message passing parallelization (with openMPI) +
- map/reduce-like design, with operators choice, as in EO
- +
- useful existing operators (parallel dynamic multi-start, static evaluations, …) +
- Portable and human-readable parameter files +
- Suspend and load population from files +
- Versatile checkpointing and logging:
+
-
+
- graphical display, +
- file dump, +
- various statistics, +
- signal catching, +
- … +
+ - Mersenne Twister random number generator (and various distributions) +
- No useless computation (sparing fitness call, functor-based calls) +
- Fast running speed, thanks to C++ +
- And more!
- Portable and human-readable parameter files -
- Suspend and load population from files -
- Versatile checkpointing and logging:
-
-
-
- graphical display, -
- file dump, -
- various statistics, -
- signal catching, -
- … -
- - Mersenne Twister random number generator (and various distributions) -
- No useless computation (sparing fitness call, functor-based calls) -
- Fast running speed, thanks to C++ -
- And more! -
-
-
-
+
-
+
Portability
-EO should work on Windows and any Un*x-like operating system with a - standard-conforming C++ development system.
- -Recent versions of EO have been tested on the following platforms: -
- --
-
- Linux x86 with GCC 3.x and 4.x -
- Linux x86_64 with GCC 3.x and GCC 4.x -
- MacOS X/Darwin PowerPC with GCC 3.x -
- MacOS X/Darwin x86 with GCC 4.x -
- Microsoft Windows using Cygwin's GCC 3.x (cygming special). -
- Microsoft Windows using Visual Studio 2003/2005; projects files - are provided. -
- Solaris SPARC with GCC 3.x -
- Solaris x86 with GCC 3.x -
Recent versions of EO uses the CMake portable build system, that permits to easily generate a build chain for your environment.
- -If you have tested EO on a system not listed here, please let - us know.
- -If you are working on a system with an older C++ compiler there - is a good chance that eo-0.9.3z.1 works. It is tested on Linux - with gcc-2.9x and several systems (IRIX, Solaris) with egcs.
-Presentations
+Portability
-A functional and "philosophical" overview of EO was presented at EA'01 conference. - You can download the paper - or the - slides, or browse them right here:
+EO should work on Windows and any Un*x-like operating system with a + standard-conforming C++ development system.
- +Recent versions of EO have been tested on the following platforms: +
+ +-
+
- Linux x86 with GCC 3.x and 4.x +
- Linux x86_64 with GCC 3.x and GCC 4.x +
- MacOS X/Darwin PowerPC with GCC 3.x +
- MacOS X/Darwin x86 with GCC 4.x +
- Microsoft Windows using Cygwin's GCC 3.x (cygming special). +
- Microsoft Windows using Visual Studio 2003/2005; projects files + are provided. +
- Solaris SPARC with GCC 3.x +
- Solaris x86 with GCC 3.x +
Recent versions of EO uses the CMake portable build system, that permits to easily generate a build chain for your environment.
+ +If you have tested EO on a system not listed here, please let + us know.
+ +If you are working on a system with an older C++ compiler there + is a good chance that eo-0.9.3z.1 works. It is tested on Linux + with gcc-2.9x and several systems (IRIX, Solaris) with egcs.
-You can also read this - PowerPoint presentation, that shows the EO philosophy. - It includes a Visual Basic macro for evolving objects in Visual Basic - for Applications.
+Presentations
-EO is described in the following scientific article:
-
M. Keijzer, J.J. Merelo, G. Romero, G., M. Schoenauer, - "Evolving - objects: A general purpose evolutionary computation - library", Artificial Evolution, 2310, 829--888 (2002).- +
A functional and "philosophical" overview of EO was presented at EA'01 conference. + You can download the paper + or the + slides, or browse them right here:
-
-
- @Article{Keijzer2001,
- title = "Evolving Objects: A General Purpose Evolutionary Computation Library ",
- author = "Maarten Keijzer and J. J. Merelo and G. Romero and M. Schoenauer",
- journal = "Artificial Evolution",
- year = "2002",
- volume = "2310",
- pages = "829--888",
- keywords = "genetic algorithms, genetic programming, evolutionary computation, metaheuristic, computational intelligence, optimization",
- URL = "http://www.lri.fr/~marc/EO/EO-EA01.ps.gz",
- size = "12 pages",
- abstract = "This paper presents the evolving objects library
- (EOlib), an object-oriented framework for evolutionary
- computation (EC) that aims to provide a flexible set of
- classes to build EC applications. EOlib design
- objective is to be able to evolve any object in which
- fitness makes sense.",
- }
-
-
-
Here is a list of some known publications that used EO:
--
-
- J.J. Gilijamse, J. Küpper, S. Hoekstra, S.Y.T. van de Meerakker, G. Meijer,
- Optimizing the Stark-decelerator beamline for the trapping of
- cold molecules using evolutionary strategies,
- Physical Review, A 73, 063410 (2006).
- Also available at arXiv - physics/0603108 (2006).
- - Johann Dreo, Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics, Genetic and Evolutionary Computation Conference, (2009). -
- Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, An Evolutionary Metaheuristic Based on State Decomposition for Domain-Independent Satisficing Planning, Twentieth International Conference on Automated Planning and Scheduling (2010). -
- Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, An Evolutionary Metaheuristic for Domain-Independent Satisficing Planning, Genetic and Evolutionary Computation Conference (2010). Silver Medal at the Human-Competitive Competition -
You can also read this + PowerPoint presentation, that shows the EO philosophy. + It includes a Visual Basic macro for evolving objects in Visual Basic + for Applications.
+ +EO is described in the following scientific article:
+
M. Keijzer, J.J. Merelo, G. Romero, G., M. Schoenauer, + "Evolving + objects: A general purpose evolutionary computation + library", Artificial Evolution, 2310, 829--888 (2002).+ + +
+
+ @Article{Keijzer2001,
+ title = "Evolving Objects: A General Purpose Evolutionary Computation Library ",
+ author = "Maarten Keijzer and J. J. Merelo and G. Romero and M. Schoenauer",
+ journal = "Artificial Evolution",
+ year = "2002",
+ volume = "2310",
+ pages = "829--888",
+ keywords = "genetic algorithms, genetic programming, evolutionary computation, metaheuristic, computational intelligence, optimization",
+ URL = "http://www.lri.fr/~marc/EO/EO-EA01.ps.gz",
+ size = "12 pages",
+ abstract = "This paper presents the evolving objects library
+ (EOlib), an object-oriented framework for evolutionary
+ computation (EC) that aims to provide a flexible set of
+ classes to build EC applications. EOlib design
+ objective is to be able to evolve any object in which
+ fitness makes sense.",
+ }
+
+
+
Here is a list of some known publications that used EO:
+-
+
- J.J. Gilijamse, J. Küpper, S. Hoekstra, S.Y.T. van de Meerakker, G. Meijer,
+ Optimizing the Stark-decelerator beamline for the trapping of
+ cold molecules using evolutionary strategies,
+ Physical Review, A 73, 063410 (2006).
+ Also available at arXiv + physics/0603108 (2006).
+ - Johann Dreo, Using Performance Fronts for Parameter Setting of Stochastic Metaheuristics, Genetic and Evolutionary Computation Conference, (2009). +
- Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, An Evolutionary Metaheuristic Based on State Decomposition for Domain-Independent Satisficing Planning, Twentieth International Conference on Automated Planning and Scheduling (2010). +
- Jacques Bibaï, Pierre Savéant, Marc Schoenauer, Vincent Vidal, An Evolutionary Metaheuristic for Domain-Independent Satisficing Planning, Genetic and Evolutionary Computation Conference (2010). Silver Medal at the Human-Competitive Competition +
Code ⤒
-Code ⤒
+Download
-Download
+The current stable release is EO 1.0. + It supports any standard-compliant C++ compiler.
-The current stable release is EO 1.0. - It supports any standard-compliant C++ compiler.
+You can obtain the latest version directly via GIT + or browse the repository online. + +
-You can obtain the latest version directly via GIT - or browse the repository online. - -
+All releases can be obtained from the SourceForge download + area.
-All releases can be obtained from the SourceForge download - area.
+Facts
-Facts
+Those statistics are automatically generated by ohloh.net, directly from the EO source code.
-Those statistics are automatically generated by ohloh.net, directly from the EO source code.
- -| - | - |
| - | - |
| + | + |
| + | + |
License
-License
+EO is distributed under the + + GNU Lesser General Public License.
-EO is distributed under the - - GNU Lesser General Public License.
- -Note that this license places copyleft restrictions on a program created with EO, but does not apply these restrictions to other software that would links with the program.
+Note that this license places copyleft restrictions on a program created with EO, but does not apply these restrictions to other software that would links with the program.
-Documentation
+Documentation
-The tutorial demonstrates that writing an evolutionary algorithm - evolving your own structures is now easy, using ready-to-use - template files. Although the tutorial has not been upgraded for some - time now and refers to version 0.9.2 of EO, it nevertheless remains the - best way to dive into EO. You can start by trying it on-line at LRI - or SourceForge, - before downloading it. The - tutorial is also included in the released - sources.
+The tutorial demonstrates that writing an evolutionary algorithm + evolving your own structures is now easy, using ready-to-use + template files. Although the tutorial has not been upgraded for some + time now and refers to version 0.9.2 of EO, it nevertheless remains the + best way to dive into EO. You can start by trying it on-line at LRI + or SourceForge, + before downloading it. The + tutorial is also included in the released + sources.
-The latest tutorial - release. -
+The latest tutorial + release. +
-The complete code is also well documented and you can look at the - generated interface - documentation.
+The complete code is also well documented and you can look at the + generated interface + documentation.
-The easiest way to create a complete new EO-project, even for new - genomes, is to use the script provided in tutorial/Templates/; see - the README in that directory and lesson 5 of the tutorial for - detail.
+The easiest way to create a complete new EO-project, even for new + genomes, is to use the script provided in tutorial/Templates/; see + the README in that directory and lesson 5 of the tutorial for + detail.
-Development ⤒
+Development ⤒
-Mailing-lists
+Mailing-lists
-EO is an open development effort; that is why we have - created mailing lists to discuss future developments, solve technical - problems, announce releases, publish patches, and discuss evolutionary - computation in general. Browse the archives or join the EO mailing lists.
+EO is an open development effort; that is why we have + created mailing lists to discuss future developments, solve technical + problems, announce releases, publish patches, and discuss evolutionary + computation in general. Browse the archives or join the EO mailing lists.
-Get involved
+Get involved
-The following resources are available, thanks to sourceforge
--
-
- EO - SourceForge Project Page -
- EO
- automatic documentation page at SF
-
- - EO
- tutorial page at SF
-
- - Releases -
- Mailing Lists -
- Message Forums -
- Bug Submission and Tracking -
- Technical Support -
- Code repository -
The following resources are available, thanks to sourceforge
+-
+
- EO + SourceForge Project Page +
- EO
+ automatic documentation page at SF
+
+ - EO
+ tutorial page at SF
+
+ - Releases +
- Mailing Lists +
- Message Forums +
- Bug Submission and Tracking +
- Technical Support +
- Code repository +
Related software
+Related software
-The softwares listed here are using EO, but they are not maintained by the EO team. - They may not be free softwares or may even be outdated.
+The softwares listed here are using EO, but they are not maintained by the EO team. + They may not be free softwares or may even be outdated.
--
-
- ParadisEO provides EO extensions for - the flexible design of single solution-based metaheuristics, - metaheuristics for multi objective optimization as well as hybrid, parallel and distributed - metaheuristics. +
- ParadisEO provides EO extensions for + the flexible design of single solution-based metaheuristics, + metaheuristics for multi objective optimization as well as hybrid, parallel and distributed + metaheuristics. -
- DegaX - is an ActiveX control which embeds EO 0.8.4. - +
- DegaX + is an ActiveX control which embeds EO 0.8.4. + -
- EASEA was a GUI that permits to build evolutionary algorithm with EO or the GAlib. - It is now a platform that allows program evolutionary algorithms on massively parallel many-core architectures. +
- EASEA was a GUI that permits to build evolutionary algorithm with EO or the GAlib. + It is now a platform that allows program evolutionary algorithms on massively parallel many-core architectures. -
- GUIDE is a GUI that allows the generation of evolutionary algorithms. It can use EO or ECJ. -
- GUIDE is a GUI that allows the generation of evolutionary algorithms. It can use EO or ECJ. +
-
+
Authors
+ +EO was started by the Geneura + Team at the University of Granada, headed by Juan Julián Merelo. The original Web site is also the only place where you + will find old releases of EO (up to 0.8.7), but beware that it is not + compatible at all with the current version.
+ +The developement team has then been reinforced by Maarten Keijzer, the C++ + wizzard, and Marc Schoenauer. + Later came Jeroen + Eggermont, who, among other things, did a lot of work on GP, + INRIA Dolphin Team, Olivier König, who did a + lot of useful additions and cleaning of the code and Jochen Küpper, working on + infrastructure maintenance.
+ +The project is now maintained by Johann Dréo, + working on it with the help of Caner Candan.
+Links
-Authors
+-
+
- COCO (COmparing Continuous Optimisers), a platform for systematic and sound comparisons of real-parameter global optimisers. COCO provides benchmark function testbeds and tools for processing and visualizing data generated by one or several optimizers. +
- The Hitch-Hiker's Guide to Evolutionary Computation, FAQ for comp.ai.genetic. +
- Wikipedia entries on Evolutionary algorithms. +
- Charles Darwin: The Origin of Species. +
EO was started by the Geneura - Team at the University of Granada, headed by Juan Julián Merelo. The original Web site is also the only place where you - will find old releases of EO (up to 0.8.7), but beware that it is not - compatible at all with the current version.
- -The developement team has then been reinforced by Maarten Keijzer, the C++ - wizzard, and Marc Schoenauer. - Later came Jeroen - Eggermont, who, among other things, did a lot of work on GP, - INRIA Dolphin Team, Olivier König, who did a - lot of useful additions and cleaning of the code and Jochen Küpper, working on - infrastructure maintenance.
- -The project is now maintained by Johann Dréo, - working on it with the help of Caner Candan.
+