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Optimization problems (Part Three) form an important class of computational problems. The key algorithms for them are the following. Greedy algorithms (Chapter 16) keep grabbing the next object that looks best. Recursive backtracking algorithms (Chapter 17) try things and, if they don’t work, backtrack and try something else. Dynamic programming (Chapter 18) solves a sequence of larger and larger instances, reusing the previously saved solutions for the smaller instances, until a solution is obtained for the given instance. Reductions (Chapter 20) use an algorithm for one problem to solve another. Randomized algorithms (Chapter 21) flip coins to help them decide what actions to take. Finally, lower bounds (Chapter 7) prove that there are...

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Cover of How to Think About Algorithms

Note

There are a zoo of optimization algorithms.