evobench 0.0.1

Benchmarks for large scale, model-based optimization.

Evobench

Evobench is a collection of benchmark problems dedicated for model-based large scale optimization.

Overview

This package contains following problems.

Discrete

• trap
• step trap
• bimodal
• step bimodal
• HIFF
• Ising Spin Glass

Continous

• trap
• multimodal
• step multimodal
• sawtooth

Getting started

pip install evobench

import evobench


trap = evobench.discrete.Trap(block_size=5, repetitions=3)
initialization = evobench.discrete.initialization.Uniform(population_size=4e3)

population = initialization.initialize_population(trap.genome_size)
fitness = trap.evaluate_population(population)

You can also evaluate single solution.

fitness = trap.evaluate_solution(population.solutions[0])

Everytime you're evaluating solutions we increment ffe counter. You can access it through benchmark instance.

print(trap.ffe)

Coming soon

We'll be adding more problems in near future. If you're looking for any particular problem, please mail us or open an issue.

We're thinking about interactive visualizations, so you can sample the space and check how it looks. It's easier than digging through definitions.

We're working on linkage quality metrics. Once they're published, we'll incorporate them to this package.