Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.-Heaps where the parent key is greater than or equal to (≥) the child keys are called max-heaps　those where it is less than or equal to (≤) are called min-heaps. Efficient (logarithmic time) algorithms are known for the two operations needed to implement a priority queue on a binary heap: inserting an element, and removing the smallest (largest) element　a min-heap (max-heap). Binary heaps are also commonly employed in the heapsort sorting algorithm, which is an in-place algorithm owing to the fact that binary heaps can be implemented as an implicit data structure, storing keys in an array and using their relative positions within that array to represent child-parent relationships.