feat(algorithms): add RandomSearch baseline optimizer

The reference baseline and the spec's recommended starting example. Per
iteration it asks the initializer for `batch_size` decisions, evaluates
each, and accumulates them. At the end it returns the full population
plus the Pareto front and (if single-objective) the best feasible
candidate. `generations` equals `iterations`; `evaluations` equals
`iterations * batch_size` (spec §12.1).

Includes a tiny single-objective sphere test problem under
`tests_support` that later algorithm tests will reuse.

src/prelude.rs

@@ -17,3 +17,5 @@ pub use crate::pareto::{
 };
 
 pub use crate::operators::{BitFlipMutation, GaussianMutation, RealBounds, SwapMutation};
+
+pub use crate::algorithms::{RandomSearch, RandomSearchConfig};