A heuristic technique is not guaranteed to be optimal, but which is nevertheless sufficient for reaching an immediate, short-term goal, with a satisfactory solution.
Examples of such:
Trial and error, Rule of thumb, Educated guess, Intuitive judgment, Guesstimate, Profiling, Common sense.
More concrete examples are:
* Sorting and prioritizing is almost always a good heuristic (by Ratios,by values).
* Minimax is a decision rule used for minimizing the possible loss for a worst case (maximum loss) scenario.
When dealing with gains, it is referred to as “maximin”—to maximize the minimum gain.
* Local search move from solution to solution in the space of candidate solutions (the search space) by applying local changes, until a maximal/optimal solution is found or a time bound is elapsed, this differs for brute force of every possibility at each step, like the full-space search algorithm.
