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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.

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. The advantage to using a greedy algorithm is that solutions to smaller instances of the problem can be straightforward and easy to understand. The disadvantage is that it is entirely possible that the most optimal short-term solutions may lead to the worst possible long-term outcome.

Greedy algorithms are often used in ad hoc mobile networking to efficiently route packets with the fewest number of hops and the shortest delay possible. They are also used in machine learning, business intelligence (BI), artificial intelligence (AI) and programming.

See also: KISS principle, Ockham's razor

 

This was last updated in February 2015

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Have you ever suffered the results of a business decision you suspect was made with a greedy algorithm?
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Hi, I'm a computer science student taking Algorithms course, I googled "greedy algorithm" because I never understood what it means, and came across your explanation, which is the best one I've found so far - easy-to-understand and intuitive. Great writing! Will visit your website often!
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Have you ever suffered the results of a business decision made using a greedy algorithm?
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My organization made a decision to go with a greedy algorithm several months ago thinking the expeditious nature of the greedy algorithm would be helpful. What we experienced was small details being tended to at the expense of the greater system. The greedy algorithm has its purpose and uses but we chose poorly and should not have made the decision to use the greedy algorithm. It ended up costing us time and money.
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