Greedy Algorithms

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I can't find a pen, so I'm going to have to write notes here!

Properties of a greedy algorithm:

• Makes the choice that looks best at the current time - this is a locally optimal choice in the hope that this leads to a globally optimal choice.
• They do not always yield optimal solutions, but for many problems they do.

The greedy method involves creating a solution through a sequence of steps.

On each step the choice made must be:

• Feasible - it has a satisfy the problem constraints
• Optimal (at least locally) - it has to be the best choice among all the feasible choices
• Irrevocable - once a choice has been made, it cannot be changed in the later steps of the algorithm

This greedy method works best when it is applied to problem with the greedy-choice property:

ly optimal solution can be obtained by from a series of local improvements from starting solution set."

That is, the greedy method suggests that one can devise an algorithm which works in stages, considering one input at a time. At each stage the locally optimal choice is made, which, when the problem is solved, create a globally optimal solution.

A more formal definition of the greedy method is:

• Given n inputs, choose a subset that satisfies the problem's constraints
• A subset that satisfies the constraints is feasible solution 
• A feasible solution that maximises or minimises a function is optimal

Often a feasible solution can be found easily but the optimal solution is difficult to find

(Adapted from M. Manjunathaiah SE2EA11 lecture notes, Introduction to Algorithms 1997, Fundamentals of Computer Algorithms 1978)

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