Module metaheuristics::hill_climbing::random_restarts

Find an approximate solution to your optimisation problem using Hill Climbing with random restarts

Here we duplicate the functionality of the metaheuristics::hill_climbing module but with slight modification - we introduce a probability of restarting the algorithm (whilst remembering the best candidate solution seen so far).

The advantage here over vanilla Hill Climbing is that this guarantees we'll never get stuck at a local maximum. In fact, given enough time, Hill Climbing with random restarts will find the globally optimal solution.

Examples

let solution = metaheuristics::hill_climbing::random_restarts::solve(
    &mut problem,
    runtime,
    probability
);

Functions

solve

Returns an approximate solution to your optimisation problem using Hill Climbing with random restarts