Software Details:
Version: 0.2.0
Upload Date: 12 May 15
Distribution Type: Freeware
Downloads: 81
EvoSynth stands for Evolutionary Computation Synthesizer.
Features:
- General features:
- Classes for individuals, populations, algorithm profiles, genomes
- support for custom randomizer
- Meta operators: proportional, sequentional and conditional combined operators
- Logging support with exporter to gnuplot, gruff and csv
- Many predefined fitness functions
- Benchmarking features:
- Diversity calculations (distance, entropy and subsequence)
- Mean, median, variance calculations for array/population
- T-test to determine statistical significance
- Most common evolutionary algorithms:
- Hillclimber (single individual and population based)
- Standard genetic algorithm, steady state GA
- Memetic algorithm
- Evolution strategies (adaptive, selfadaptive and derandomized)
- Local search (hillclimber, threshold acceptance, simulated annealing, great deluge, record-to-record travel)
- Coevolutionary algorithms (round robin and balanced)
- Selection strategies:
- Identity
- Random selection
- Best selection
- n-stage tournament selection
- Tournament selection
- Fitness proportional selection
- Roulette wheel selection
- Mutations:
- Identity
- One gene flipping, binary mutation, efficient binary mutation
- Exchange mutation, inversion mutation, mixing mutation, shifting mutation
- Uniform real mutation, Gauss mutation, self-adaptive Gauss mutation
- Recombinations:
- Identity
- One-point-crossover, k-point-crossover, uniform crossover
- Arithmetic crossover
- Ordered recombination, partially mapped crossover, edge recombination
- Global uniform crossover, global arithmetic crossover
What is new in this release:
- Added SP_k problem to binary benchmark functions
- Added EvoSynth.rand_element to retrieve a random element from a array
- Added EvoBench (benchmarking for evolutionary algorithms) module
What is new in version 0.1.1:
- New benchmarking features like diversity calculations (distance, entropy and subsequence), mean, median, variance calculations for array/population and t-test to determine statistical significance.
- rakefile: dependency cleanup.
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