1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87
// file: lib.rs // // Copyright 2015-2016 The RsGenetic Developers // // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. //! # RsGenetic //! //! RsGenetic provides a simple framework for genetic algorithms. //! You need to provide the definition of a Phenotype (also known as an Individual), //! define how crossover and mutation work, present a fitness function, choose some settings //! and this library takes care of the rest. //! //! # Installation //! //! You can use this library by adding the following lines to your `Cargo.toml` file: //! //! ```ignore //! [dependencies] //! rsgenetic = "0.13" //! ``` //! //! and adding `extern crate rsgenetic;` to your crate root. //! //! # Features //! ## Available Simulators //! //! There is currently only one, sequential, simulator. This simulator will run //! the genetic algorithm on a single thread. //! //! ## Available Selection Types //! //! There are currently four selection types available: //! //! * Maximize //! * Tournament //! * Stochastic //! //! There is a short explanation for each of these below. For more information, look at the //! documentation of individual selectors. //! //! ### Maximize //! //! Maximize takes 1 parameter: the count. This is half the number of parents //! that will be selected. Selection happens by taking the top `count` individuals, //! ranked by fitness. The resulting number of parents is `count`. //! //! ### Tournament //! //! Tournament takes 2 parameters: the number of tournaments (`count`) and `participators`, which indicates how //! many phenotypes participate in a tournament. The resulting number of parents is `count`. //! //! ### Stochastic //! //! Stochastic takes 1 parameter: the count. The resulting number of parents is `count`. //! //! ## Early Stopping //! //! If you wish, you can stop early if the fitness value of the best performing Phenotype //! doesn't improve by a large amount for a number of iterations. This can be done by calling the //! `set_early_stop(delta: Fitness, n_iters: u32)` function on the `SimulatorBuilder`. //! //! # Examples //! //! See the `examples` directory in the repository for examples. #![warn(missing_docs)] extern crate rand; extern crate time; /// Contains the definition of a Phenotype. pub mod pheno; /// Contains implementations of Simulators, which can run genetic algorithms. pub mod sim; /// Contains code used by unit tests. mod test;