Day 21: Genetic Algorithms vs. Brute Force: A Benchmark Comparison
To conclude Week 3, let’s address one of the most common questions developers ask when learning about genetic algorithms: How do they perform compared to brute-force solutions? This is especially relevant when working on combinatorial problems, such as the Traveling Salesperson Problem (TSP) or scheduling tasks. Genetic algorithms promise that they offer reasonable solutions in a fraction of the time it takes brute-force methods to find optimal ones. But how does this actually play out?
Today, we’ll benchmark a simple scenario using both approaches and compare execution time and solution quality. We’ll use the TSP with 8 cities as our problem space. This size is large enough to make brute-force non-trivial, but still solvable within a reasonable time.