Solution: A d-heap is similar to that of a binary heap except that binary heaps have two children and d-heaps have d children.

Solution: d-heap is much shallower than a binary heap with respect to performance efficiency of insert and delete operations.

Solution: Find operation in a d-heap cannot be performed as in other heaps. This is the main weakness of d-heap.

Solution: Unlike find operation, which cannot be performed in a d-heap, the task of merging two d-heaps is very difficult.

Solution: The run time efficiency of an insertion algorithm in a d-heap is found to be O(logd N) where d is the number of children.

Solution: Since, the delete-min operation is more expensive and the heap is shallow, the minimum of d elements can be found using d-1 comparisons.

Solution: The two basic operations performed in a d-heap are insert and delete-min operations.

Solution: The run time efficiency of a delete-min algorithm using d-1 comparisons is mathematically found to be O(d logd N).

Solution: The other operations that can be performed in a d-heap are increasekey, decreasekey, buildheap and delete.

Solution: d-ary heap is a priority queue based data structure that is a generalization of binary heaps.