ghc-moo

Moo library provides building blocks to build custom genetic algorithms in
Haskell. They can be used to find solutions to optimization and search
problems.
Variants supported out of the box: binary (using bit-strings) and continuous
(real-coded). Potentially supported variants: permutation, tree, hybrid
encodings (require customizations).
Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and
uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX
crossover. Selection operators: roulette, tournament, and stochastic universal
sampling (SUS); with optional niching, ranking, and scaling.
Replacement strategies: generational with elitism and steady state.
Constrained optimization: random constrained initialization, death penalty,
constrained selection without a penalty function. Multi-objective optimization:
NSGA-II and constrained NSGA-II.

          

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License: BSD-3-Clause
URL: https://hackage.haskell.org/package/moo