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Evolving Objects

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EO is a template-based, ANSI-C++ evolutionary computation library which helps you to write your own stochastic optimization algorithms insanely fast. With the help of EO, you can easily design evolutionary algorithms that will find solutions to virtually all kind of hard optimization problems ... [More] , from continuous to combinatorial ones. 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. [Less]

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0 current contributors

0 since last commit

6 users on Open Hub

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5.0
 
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Mostly written in language not available
Licenses: lgpl

ParadisEO

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ParadisEO is a C++ white-box object-oriented software framework for to the reusable design of metaheuristics. * Portable on: Windows, Unix and MacOS * Parallel and distributed architectures (MPI) * Grids (Globus, Condor-G/MW) It is composed of 4 interconnected modules: * ParadisEO-EOfor ... [More] population-based metaheuristics (evolutionary algorithms, particle swarm optimization, evolution strategy, differential evolution...) * ParadisEO-MO for solution-based metaheuristics (local search, simulated annealing, tabu search, iterated local search, variable neighborhood search...) * ParadisEO-MOEO for multiobjective optimization * ParadisEO-PEO for hybrid, parallel and distributed metaheuristics * ParadisEO-SMP for memory-shared parrallel metaheuristics [Less]

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1 current contributors

0 since last commit

5 users on Open Hub

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5.0
 
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Mostly written in language not available
Licenses: lgpl

MOEA Framework

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  Analyzed 11 months ago

The MOEA Framework is an open source Java library for developing and experimenting with multiobjective evolutionary algorithms (MOEAs) and other general-purpose optimization algorithms and metaheuristics. A number of algorithms are provided out-of-the-box, including NSGA-II, ε-MOEA, GDE3 and MOEA/D. ... [More] In addition, third-party tools like JMetal and PISA directly integrate with the MOEA Framework. The MOEA Framework targets an academic audience, providing the resources necessary to rapidly design, develop, execute and statistically test optimization algorithms. This includes over 40 test problems from the literature, and a suite of statistical tools for comparing and analyzing algorithm performance. [Less]

71K lines of code

1 current contributors

11 months since last commit

1 users on Open Hub

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5.0
 
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Gentech

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  Analyzed 11 months ago

Gentech, A Genetic Algorithm Solver This genetic algorithm follows the natural process of meiosis.

10.7K lines of code

0 current contributors

about 2 years since last commit

1 users on Open Hub

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0.0
 
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