Remove gene pool from rosomaxa

reinterpretcat · Oct 5, 2024 · e2ee0cd · e2ee0cd
1 parent 49c0f84
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diff --git a/CHANGELOG.md b/CHANGELOG.md
@@ -19,6 +19,7 @@ are already published. So, I stick to it for now.
 ### Removed
 
 * replace `compare_floats` with built-in `total_cmp`
+* gene pool in rosomaxa
 
 
 ## [1.24.0] 2024-07-13

diff --git a/rosomaxa/src/population/rosomaxa.rs b/rosomaxa/src/population/rosomaxa.rs
@@ -125,14 +125,13 @@ where
     }
 
     fn select<'a>(&'a self) -> Box<dyn Iterator<Item = &Self::Individual> + 'a> {
-        #![allow(clippy::unnecessary_cast)]
         match &self.phase {
             RosomaxaPhases::Exploration { network, coordinates, selection_size, statistics, .. } => {
                 let random = self.environment.random.as_ref();
 
                 let (elite_explore_size, node_explore_size) = match *selection_size {
                     value if value > 6 => {
-                        let ratio = statistics.improvement_1000_ratio as f64;
+                        let ratio = statistics.improvement_1000_ratio;
                         let elite_exlr_prob = (1. - 1. / (1. + E.powf(-10. * (ratio - 0.166)))) as Float;
                         let elite_size = (1..=2).fold(0, |acc, idx| {
                             acc + if random.is_hit(elite_exlr_prob / idx as Float) { 2 } else { 1 }
@@ -236,25 +235,12 @@ where
                         individuals.drain(0..4).collect(),
                     );
 
-                    let initial = std::mem::take(individuals);
-                    let initial = initial.into_iter().map(init_individual).collect::<Vec<_>>();
-                    initial.iter().for_each(|individual| network.store(individual.deep_copy(), 0));
-
-                    // create gene pool to keep track of population progress
-                    let gene_pool_size = self.config.selection_size.clamp(4, 8);
-                    let gene_pool_selection_size = (gene_pool_size / 2).max(4);
-                    let mut gene_pool = Elitism::new_with_dedup(
-                        self.objective.clone(),
-                        self.environment.random.clone(),
-                        gene_pool_size,
-                        gene_pool_selection_size,
-                        create_dedup_fn(0.05),
-                    );
-                    gene_pool.add_all(initial);
+                    std::mem::take(individuals)
+                        .into_iter()
+                        .for_each(|individual| network.store(init_individual(individual), 0));
 
                     self.phase = RosomaxaPhases::Exploration {
                         network,
-                        gene_pool,
                         coordinates: vec![],
                         statistics: statistics.clone(),
                         selection_size,
@@ -263,7 +249,6 @@ where
             }
             RosomaxaPhases::Exploration {
                 network,
-                gene_pool,
                 coordinates,
                 statistics: old_statistics,
                 selection_size: old_selection_size,
@@ -277,8 +262,6 @@ where
                     *old_statistics = statistics.clone();
                     *old_selection_size = selection_size;
 
-                    Self::reintroduce_gene_pool(network, &self.elite, gene_pool, statistics, &self.config);
-
                     Self::optimize_network(network, statistics, &self.config);
 
                     Self::fill_populations(network, coordinates, self.environment.random.as_ref());
@@ -296,31 +279,6 @@ where
         best_known.map_or(true, |best_known| self.objective.total_order(individual, best_known) != Ordering::Greater)
     }
 
-    fn reintroduce_gene_pool(
-        network: &mut IndividualNetwork<O, S>,
-        elite: &Elitism<O, S>,
-        gene_pool: &mut Elitism<O, S>,
-        statistics: &HeuristicStatistics,
-        config: &RosomaxaConfig,
-    ) {
-        let frequency = match statistics.speed {
-            HeuristicSpeed::Slow { .. } => config.rebalance_memory.min(10),
-            _ => (config.rebalance_memory / 2).max(20),
-        };
-
-        if statistics.generation > 0 && statistics.generation % frequency == 0 {
-            network.store_batch(
-                gene_pool.select().map(|i| i.deep_copy()).collect(),
-                statistics.generation,
-                init_individual,
-            );
-
-            if let Some(best_known) = elite.select().next() {
-                gene_pool.add(best_known.deep_copy());
-            }
-        }
-    }
-
     fn optimize_network(
         network: &mut IndividualNetwork<O, S>,
         statistics: &HeuristicStatistics,
@@ -429,7 +387,6 @@ where
     },
     Exploration {
         network: IndividualNetwork<O, S>,
-        gene_pool: Elitism<O, S>,
         coordinates: Vec<Coordinate>,
         statistics: HeuristicStatistics,
         selection_size: usize,