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Algorithms Articles
Page 14 of 39
Difference Between Greedy Method and Dynamic Programming
In this post, we will understand the differences between the greedy algorithm and dynamic programming methods.Greedy algorithmIt is an algorithmic paradigm that builds up on a solution in parts, step by step. The next step is chosen such that it gives the most obvious and immediate benefit.Problems that involve choosing local optimal values will help in choosing the global optimal values/solution to the problem. Such ate the problems associated with greedy algorithm.There is no surety that a greedy algorithm would lead to an optimal solution.An optimal choice is made at every stage of the problem, i.e the local optimal solution.It ...
Read MoreDifference Between Prim's and Kruskal's Algorithm
In this post, we will understand the differences between Prim's and Kruskal's algorithms.Kruskal's algorithm for Mininum Spanning Tree (MST)When a connected and undirected graph is given, a spanning tree of such a graph is the subgraph which is a tree that connects all of the vertices.A single graph can have multiple spanning trees.A minimum spanning tree (MST) (also known as minimum weight spanning tree) for a weighted, connected and undirected graph is a spanning tree that weighs less than or equal to the weight of every other spanning tree.The weight of a spanning tree is determined by adding the weights ...
Read MoreAlgorithm to construct an Expression Tree in Data Structure
Expression treesExpression trees are those in which the leaf nodes have the values to be operated, and internal nodes contain the operator on which the leaf node will be performed.Example4 + ((7 + 9) * 2) will have an expression tree as followsAlgorithm to Construct an Expression TreeLet T be the expression tree.If T is not NULL: If T->data is an operand: return T.data A = solve(T.left) B = solve(T.right) --> Calculate operator for 'T.data' on A and B, and call recursively, return calculate(A, B, T.data)How to construct an expression tree?To construct an Expression Tree for ...
Read MoreYen's k-Shortest Path Algorithm in Data Structure
Instead of giving a single shortest path, Yen’s k-shortest path algorithm gives k shortest paths so that we can get the second shortest path and the third shortest path and so on.Let us consider a scenario that we have to travel from place A to place B and there are multiple routes available between place A and place B, but we have to find the shortest path and neglect all the paths that are less considered in terms of its time complexity in order to reach the destination.Let us understand with an example-Consider the given example as the bridge which ...
Read MoreFloyd Cycle Detection Algorithm to detect the cycle in a linear Data Structure
Floyd Cycle is one of the cycle detection algorithms to detect the cycle in a given singly linked list.In the Floyd Cycle algorithm, we have two pointers that initially point at the head. In Hare and Tortoise’s story, Hare moves twice as fast as Tortoise, and whenever the hare reaches the end of the path, the tortoise reaches the middle of the path.AlgorithmInitialize Hare and Tortoise at the head node of the List.Initially, the hare moves twice as fast as the tortoise.Move the hare and tortoise both and find if the hare reaches the end of the Linked List, return ...
Read MoreAuto-complete feature using Trie
We have a Trie, and when a user enters a character, we have to show the matching string the Trie. This feature we call it as auto-completion. For example, if a Trie contains "xyzzzz, ""xyz, " "xxxyyxzzz" and when the user enter xy, then we have to show them xyzzzz, xyz, etc.., Steps to achieve the result.Search for the string using the standard Trie algorithm.If the string is not present, then return -1.If the string is present and is the end of a word in Trie, then print the string.If the matching string doesn't have any node, then return.Else print ...
Read MoreSegment Trees in Data Structure
In this section we will see what is the segment tree. Before discussing that, let us see one problem.Suppose we have an array arr[0, …, n-1], We can do following operations −Find the sum of elements from index l to r, where 0 ≤ l ≤ r ≤ n-1Change the value of a specified element of the array to a new value x. We need to do arr[i] = x. The i in range 0 to n – 1.We can solve this problem by using the Segment tree. The segment tree can help us to get the sum and query ...
Read MoreInterval Trees in Data Structure
In this section we will see what is the interval tree. As the name suggests, that the interval trees are the trees which are associated with the intervals. So before discussing about the interval trees, let us see the elementary intervals.An interval is basically a range. So if one interval is written as [a, b] it indicates that the range is starting from a, and ending at b.Now suppose there is an interval [10, 20]. So there are three range values. First one is -∞ to 10, 10 to 20 and finally 20 to ∞Now, suppose we will create second ...
Read MoreB-tree Deletion in Data Structure
Here we will see, how to perform the deletion of a node from B-Tree. Suppose we have a BTree like below −Example of B-Tree −Deletion has two parts. At first we have to find the element. That strategy is like the querying. Now for deletion, we have to care about some rules. One node must have at-least m/2 elements. So if we delete, one element, and it has less than m-1 elements remaining, then it will adjust itself. If the entire node is deleted, then its children will be merged, and if their size issame as m, then split them ...
Read MoreB-tree Query in Data Structure
Here we will see, how to perform the searching in B-Tree. The B-Tree searching is also known as B-Tree Querying. Suppose we have a B-tree like below −Example of B-Tree −The searching technique is very similar to the binary search tree. Suppose we want to search 66 from the above tree. So we will start from root, now 66 is larger than root element 46. So we will move to the right child of the root. Then the right child has more than one element. The elements are sorted, they are [56, 81]. Our target key is larger than 56, ...
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