Global minimum / Local minimum

Statement

In optimization, a global minimum is the lowest value of a cost function over the entire domain; a local minimum is a point where the function is lower than at nearby points but not necessarily the lowest overall. Kirkpatrick, Gelatt, and Vecchi formalized these concepts in the context of simulated annealing for escaping local minima.