docs(examples): add toy_nsga2, random_search, and custom_optimizer

The three runnable examples called out in spec §18.5 / §19. All open
with `use heuropt::prelude::*;` so they double as a check that the
prelude is sufficient on its own:

- toy_nsga2.rs: Schaffer N.1 solved with NSGA-II.
- random_search.rs: 2D sphere solved with RandomSearch.
- custom_optimizer.rs: a minimal hill-climber implementing
  `Optimizer<P>` directly, demonstrating spec §2.3.

examples/toy_nsga2.rs

@@ -0,0 +1,42 @@
+//! Solve the Schaffer N.1 two-objective problem with NSGA-II.
+//!
+//! Run with:
+//!
+//! ```bash
+//! cargo run --example toy_nsga2
+//! ```
+
+use heuropt::prelude::*;
+
+struct SchafferN1;
+
+impl Problem for SchafferN1 {
+    type Decision = Vec<f64>;
+
+    fn objectives(&self) -> ObjectiveSpace {
+        ObjectiveSpace::new(vec![Objective::minimize("f1"), Objective::minimize("f2")])
+    }
+
+    fn evaluate(&self, x: &Vec<f64>) -> Evaluation {
+        let v = x[0];
+        Evaluation::new(vec![v * v, (v - 2.0).powi(2)])
+    }
+}
+
+fn main() {
+    let initializer = RealBounds::new(vec![(-5.0, 5.0)]);
+    let variation = GaussianMutation { sigma: 0.2 };
+    let config = Nsga2Config { population_size: 60, generations: 80, seed: 42 };
+    let mut optimizer = Nsga2::new(config, initializer, variation);
+
+    let result = optimizer.run(&SchafferN1);
+
+    println!("Final population: {}", result.population.len());
+    println!("Pareto front size: {}", result.pareto_front.len());
+    println!("Total evaluations: {}", result.evaluations);
+    println!("First few front points (f1, f2):");
+    for c in result.pareto_front.iter().take(8) {
+        let o = &c.evaluation.objectives;
+        println!("  ({:.4}, {:.4})", o[0], o[1]);
+    }
+}