## Greedy approach vs Dynamic Programming

Greedy approach and Dynamic programming both are used for solving optimisation problems. However often we need to use DP since optimal solution cannot be guaranteed by a greedy algorithm. Consider Knapsack problem We could solve it by brute-force, by generating all possibilities of choosing a subset of n items and selecting […]

## Knapsack problem (Finding selected items)

In the last post, we learned about Knapsack problem and also found an efficient solution to the problem using Dynamic programming. A little recap Let given weights & values of n items to be put in a knapsack of capacity W ie. We’ve 2 integer arrays value[0..n-1] and weight[0…n-1]. The objective is to find out […]

## Knapsack Problem (Dynamic Programming)

Problem statement Let given weights & values of n items to be put in a knapsack of capacity W ie. We’ve 2 integer arrays value[0..n-1] and weight[0…n-1]. The objective is to find out the maximum value subset of value[] array such that sum of weight of subset is smaller or equal […]

## Multiset Partitioning Problem

In mathematics, a partition of a set is a grouping of its elements into non-empty subsets, in such a way that number of elements in the original set always equals to the sum of number of elements in each partition. Equivalently, a family of sets P is a partition of X if and only if […]

## Quicksort worst-case and averages-case analysis

Quicksort algorithm was developed by a British computer scientist Tony Hoare in 1959.  “Quick Sort” is capable of sorting a list of data elements significantly faster (twice or thrice faster) than any of the common sorting algorithms and that’s why it is the favourite topic of interviewers in programming interviews. It is one […]

## N Queen Problem Analysis

The N Queen is the problem of placing N chess queens on an N×N chessboard so that no two queens attack each other. For a larger N, this problem couldn’t be solved in polynomial time. So, it is an NP-Complete problem. However, this problem could be solved by backtracking in non-polynomial time for a […]

## Backtracking

Backtracking is a general algorithm for finding solutions to some computational problems, that incrementally builds candidates to the solutions, and abandons a candidate (“backtracks”) as soon as it determines that the candidate cannot possibly be completed to a valid solution.