Iterative Improvement Algorithms and Hill-Climbing

Another way of solving the local maxima problem involves repeated explorations of the problem space. "Random-restart hill-climbing conducts a series of hill-climbing searches from randomly generated initial states, running each until it halts or makes no discernible progress". This enables comparison of many optimization trials, and finding a most optimal solution thus becomes a question of using sufficient iterations on the data.