An Implementation of Metaheuristics: Genetic Algorithms, Simulated Annealing & Particle Swarm Optimization to find approximate solutions to a Knapsack problem.
These intelligent optimization algorithms effectively search any high-dimensional domain to find good approximate global maxima/minima. Though applied to knapsack (a discrete problem set) all techniques are easily modified to handle continuous search domains. In fact, these are applicable to any problem that can be posed mathematically.
Underlying philosophy: Given a sufficiently complicated problem set, write an algorithm at writes an algorithm.