swaits
974011796e
Dorigo-style Ant System for permutation problems on a complete graph: each generation, every ant constructs a tour by probabilistically picking the next node from those it has not yet visited, weighted by `τ_ij^α · η_ij^β` where τ is the pheromone level on edge (i, j) and η is the heuristic desirability (1 / distance, here). After all ants finish, pheromone evaporates by a factor `(1 - ρ)` and is reinforced on each ant's tour proportional to that tour's quality. Decision type is `Vec<usize>` (a permutation of 0..n_cities). The user supplies a distance matrix and the n_cities is inferred. Single-objective only (the cost is total tour length, which the Problem evaluates). Tests build a 5-city ring and verify ACO finds a near-optimal tour, plus deterministic reruns and panic on multi-objective.
37 lines
757 B
Rust
37 lines
757 B
Rust
//! Built-in reference optimizers.
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pub mod ant_colony_tsp;
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pub mod cma_es;
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pub mod differential_evolution;
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pub mod genetic_algorithm;
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pub mod hill_climber;
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pub mod ibea;
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pub mod moead;
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pub mod mopso;
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pub mod nsga2;
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pub mod nsga3;
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pub mod paes;
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pub(crate) mod parallel_eval;
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pub mod particle_swarm;
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pub mod random_search;
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pub mod simulated_annealing;
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pub mod spea2;
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pub mod tabu_search;
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pub use ant_colony_tsp::*;
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pub use cma_es::*;
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pub use differential_evolution::*;
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pub use genetic_algorithm::*;
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pub use hill_climber::*;
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pub use ibea::*;
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pub use moead::*;
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pub use mopso::*;
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pub use nsga2::*;
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pub use nsga3::*;
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pub use paes::*;
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pub use particle_swarm::*;
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pub use random_search::*;
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pub use simulated_annealing::*;
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pub use spea2::*;
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pub use tabu_search::*;
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