Heuristics are useful for finding approximate solutions in problems where exact solutions are too slow to compute.

Heuristics are strategies or guidelines that help find approximate solutions when exact methods are too slow or difficult to implement, particularly in problems with large input sizes or complex constraints. In competitive programming, heuristic methods like greedy algorithms, local search, or genetic algorithms can provide 'good enough' solutions within time limits, even if they don't guarantee the best solution. While heuristics are powerful for NP-hard problems, understanding their limitations and when to apply them is key. The balance between optimality and efficiency often determines the success of heuristic approaches in contests.