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Complexity of Algorithm The complexity of an algorithm(M) is the function f(n) which gives the running time and/or storage space requirement of the algorithm in terms of the size(n) of the input data. Mostly, the storage space required by an algorithm is simply a multiple of the data size(n). Generally, Read more…

Divide & Conquer Binary search Multiplication of two n-bits numbers Quick Sort Heap Sort Merge Sort Greedy Method Knapsack (Fractional) Problem Minimum Cost Spanning Tree Kruskal‟s algorithm Prim‟s algorithm Single Source Shortest Path Problem Dijkstra’s Algorithm Dynamic Programming All Pair Shortest Path-Floyed Algorithm Chain Matrix Multiplication Longest Common Subsequence (LCS) Read more…

Introduction The Branch and Bound algorithm is a powerful technique for solving optimization problems that has been successfully applied to a wide range of problems. Its effectiveness/performance depends on the quality of the bounds used to prune the search space, as well as the problem’s structure of the problem being Read more…

Introduction It is one of the very important types of algorithms. Definition Backtracking is a general algorithmic technique that is used to solve a wide range of problems, including combinatorial optimization problems, constraint satisfaction problems, and other problems that involve finding a solution among a large set of possible solutions. Read more…

Introduction The dynamic Programming method is a famous algorithmic principle used widely in several applications. Definition Dynamic programming is a technique for solving complex problems by breaking them down into smaller & simpler sub-problems and solving each sub-problem only once, saving the results in a table and reusing them when Read more…

Introduction The greedy principle is an algorithm design paradigm in which the algorithm makes the locally optimal choice at each step in the hope of finding a globally optimal solution. Definition The greedy principle is a heuristic algorithmic technique in computer science where an optimal solution is reached by making Read more…

Introduction The divide and conquer principle is a fundamental algorithm design paradigm in computer science. Definition The divide and conquer principle is a common algorithmic technique used to solve problems by breaking them down into smaller sub-problems, solving each sub-problem independently, and combining the solutions of the sub-problems to form Read more…

Click this link for Algorithm Example          Introduction Algorithm is a basic tool and is the first step of problem-solving that helps in getting the effective solution of a simple problem. Definition An algorithm is a set of sequential step by step procedure, each of which has Read more…