GREEDY ALGORITHM
A greedy algorithm is a mathematical process that looks for simple, easy-to-implement solutions to complex, multi-step problems by deciding which next step will provide the most obvious benefit.
Greedy algorithms are similar to dynamic programming algorithms in that the solutions are both efficient and optimal if the problem exhibits some particular sort of substructure. A greedy algorithm builds a solution by going one step at a time through the feasible solutions, applying a heuristic to determine the best choice. A heuristic applies an insight to solving the problem, such as always choose the largest, smallest, etc.
Such algorithms are called greedy because while the optimal solution to each smaller instance will provide an immediate output, the algorithm doesn’t consider the larger problem as a whole. Once a decision has been made, it is never reconsidered.
Greedy algorithms work by recursively constructing a set of objects from the smallest possible constituent parts. Recursion is an approach to problem solving in which the solution to a particular problem depends on solutions to smaller instances of the same problem.
Advantages of greed algorithm * Always taking the best available choice is usually easy. * It usually requires sorting the choices. * Solutions to smaller instances of the problem can be straightforward and easy to understand. * Repeatedly taking the next available best choice is usually linear work. * But don't forget the cost of sorting the choices. * Much cheaper than exhaustive search. * Much cheaper than most other algorithms.
Disadvantages of greed algorithm * Greedy algorithms don't work for some problems. * Despite their simplicity, correct greedy algorithms can be subtle. * It's easy to fool yourself into believing an incorrect greedy algorithm is correct. * Using greed is not an automatic. * It is entirely possible that the most optimal short-term solutions may lead to the worst possible long-term outcome.
Application of greedy algorithm
The technique is used in the following graph algorithms which have many practical applications: 1. Dijkstra's algorithm for finding shortest path to all nodes given a start node.
2. Prim's algorithm for finding a minimum spanning tree.
3. Huffman trees for data compression.

 Greedy Algorithms, Chapter 17 in Introduction to Algorithms by Thomas Cormen, Charles Leiserson, and Ronald Rivest, MIT Press, 1999.
 Greedy Algorithms, Chapter 5 in Algorithms by Sanjoy Dasgupta, Christos Papadimitriou, and Umesh Vizirani, McGraw-Hill, 2008