– Local search algorithms (hill-climbing…)
Iterative algorithm:
– Start with some initial solution
– Explore the surrounding area of the current solution
– Replace the current solution with a better one z Different approaches depending on the choice criteria and termination criteria
– Stochastic: random selection
Hill climbing: only allow neighbours to move who improve the current z Greedy
– the best neighbour, Anxious
– improving the first neighbour’s sideways movement
– allows moves with the same fitness level